Merge pull request #2354 from lissyx/run-examples-taskcluster
Run examples on TaskCluster
This commit is contained in:
lissyx
GitHub
commit
f98bfefc77
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@ -17,16 +17,6 @@ const LM_ALPHA = 0.75;
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// The beta hyperparameter of the CTC decoder. Word insertion bonus.
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const LM_BETA = 1.85;
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// These constants are tied to the shape of the graph used (changing them changes
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// the geometry of the first layer), so make sure you use the same constants that
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// were used during training
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// Number of MFCC features to use
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const N_FEATURES = 26;
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// Size of the context window used for producing timesteps in the input vector
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const N_CONTEXT = 9;
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let VersionAction = function VersionAction(options) {
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options = options || {};
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options.nargs = 0;
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@ -55,15 +45,14 @@ function totalTime(hrtimeValue) {
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console.error('Loading model from file %s', args['model']);
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const model_load_start = process.hrtime();
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let model = new Ds.Model(args['model'], N_FEATURES, N_CONTEXT, args['alphabet'], BEAM_WIDTH);
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let model = new Ds.Model(args['model'], args['alphabet'], BEAM_WIDTH);
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const model_load_end = process.hrtime(model_load_start);
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console.error('Loaded model in %ds.', totalTime(model_load_end));
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if (args['lm'] && args['trie']) {
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console.error('Loading language model from files %s %s', args['lm'], args['trie']);
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const lm_load_start = process.hrtime();
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model.enableDecoderWithLM(args['alphabet'], args['lm'], args['trie'],
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LM_ALPHA, LM_BETA);
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model.enableDecoderWithLM(args['lm'], args['trie'], LM_ALPHA, LM_BETA);
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const lm_load_end = process.hrtime(lm_load_start);
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console.error('Loaded language model in %ds.', totalTime(lm_load_end));
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}
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@ -106,7 +95,7 @@ const ffmpeg = spawn('ffmpeg', [
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]);
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let audioLength = 0;
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let sctx = model.setupStream(AUDIO_SAMPLE_RATE);
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let sctx = model.createStream(AUDIO_SAMPLE_RATE);
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function finishStream() {
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const model_load_start = process.hrtime();
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@ -119,7 +108,7 @@ function finishStream() {
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function intermediateDecode() {
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finishStream();
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sctx = model.setupStream(AUDIO_SAMPLE_RATE);
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sctx = model.createStream(AUDIO_SAMPLE_RATE);
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}
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function feedAudioContent(chunk) {
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@ -8,7 +8,7 @@
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},
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"dependencies": {
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"argparse": "^1.0.10",
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"deepspeech": "^0.4.1",
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"deepspeech": "^0.6.0-alpha.5",
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"node-vad": "^1.1.1",
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"util": "^0.11.1"
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},
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@ -0,0 +1,30 @@
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#!/bin/bash
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set -xe
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THIS=$(dirname "$0")
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pushd ${THIS}
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source ../tests.sh
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npm install $(get_npm_package_url)
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npm install
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node ./index.js --audio $HOME/DeepSpeech/audio/2830-3980-0043.wav \
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--lm $HOME/DeepSpeech/models/lm.binary \
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--trie $HOME/DeepSpeech/models/trie \
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--model $HOME/DeepSpeech/models/output_graph.pbmm \
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--alphabet $HOME/DeepSpeech/models/alphabet.txt
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node ./index.js --audio $HOME/DeepSpeech/audio/4507-16021-0012.wav \
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--lm $HOME/DeepSpeech/models/lm.binary \
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--trie $HOME/DeepSpeech/models/trie \
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--model $HOME/DeepSpeech/models/output_graph.pbmm \
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--alphabet $HOME/DeepSpeech/models/alphabet.txt
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node ./index.js --audio $HOME/DeepSpeech/audio/8455-210777-0068.wav \
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--lm $HOME/DeepSpeech/models/lm.binary \
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--trie $HOME/DeepSpeech/models/trie \
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--model $HOME/DeepSpeech/models/output_graph.pbmm \
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--alphabet $HOME/DeepSpeech/models/alphabet.txt
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popd
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@ -20,8 +20,11 @@ class Audio(object):
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CHANNELS = 1
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BLOCKS_PER_SECOND = 50
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def __init__(self, callback=None, device=None, input_rate=RATE_PROCESS):
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def __init__(self, callback=None, device=None, input_rate=RATE_PROCESS, file=None):
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def proxy_callback(in_data, frame_count, time_info, status):
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#pylint: disable=unused-argument
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if self.chunk is not None:
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in_data = self.wf.readframes(self.chunk)
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callback(in_data)
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return (None, pyaudio.paContinue)
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if callback is None: callback = lambda in_data: self.buffer_queue.put(in_data)
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@ -42,9 +45,13 @@ class Audio(object):
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'stream_callback': proxy_callback,
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}
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self.chunk = None
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# if not default device
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if self.device:
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kwargs['input_device_index'] = self.device
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elif file is not None:
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self.chunk = 320
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self.wf = wave.open(file, 'rb')
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self.stream = self.pa.open(**kwargs)
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self.stream.start_stream()
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@ -96,8 +103,8 @@ class Audio(object):
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class VADAudio(Audio):
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"""Filter & segment audio with voice activity detection."""
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def __init__(self, aggressiveness=3, device=None, input_rate=None):
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super().__init__(device=device, input_rate=input_rate)
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def __init__(self, aggressiveness=3, device=None, input_rate=None, file=None):
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super().__init__(device=device, input_rate=input_rate, file=file)
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self.vad = webrtcvad.Vad(aggressiveness)
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def frame_generator(self):
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@ -121,6 +128,9 @@ class VADAudio(Audio):
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triggered = False
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for frame in frames:
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if len(frame) < 640:
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return
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is_speech = self.vad.is_speech(frame, self.sample_rate)
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if not triggered:
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@ -153,23 +163,25 @@ def main(ARGS):
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print('Initializing model...')
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logging.info("ARGS.model: %s", ARGS.model)
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logging.info("ARGS.alphabet: %s", ARGS.alphabet)
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model = deepspeech.Model(ARGS.model, ARGS.n_features, ARGS.n_context, ARGS.alphabet, ARGS.beam_width)
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model = deepspeech.Model(ARGS.model, ARGS.alphabet, ARGS.beam_width)
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if ARGS.lm and ARGS.trie:
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logging.info("ARGS.lm: %s", ARGS.lm)
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logging.info("ARGS.trie: %s", ARGS.trie)
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model.enableDecoderWithLM(ARGS.alphabet, ARGS.lm, ARGS.trie, ARGS.lm_alpha, ARGS.lm_beta)
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model.enableDecoderWithLM(ARGS.lm, ARGS.trie, ARGS.lm_alpha, ARGS.lm_beta)
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# Start audio with VAD
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vad_audio = VADAudio(aggressiveness=ARGS.vad_aggressiveness,
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device=ARGS.device,
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input_rate=ARGS.rate)
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input_rate=ARGS.rate,
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file=ARGS.file)
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print("Listening (ctrl-C to exit)...")
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frames = vad_audio.vad_collector()
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# Stream from microphone to DeepSpeech using VAD
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spinner = None
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if not ARGS.nospinner: spinner = Halo(spinner='line')
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stream_context = model.setupStream()
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if not ARGS.nospinner:
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spinner = Halo(spinner='line')
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stream_context = model.createStream()
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wav_data = bytearray()
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for frame in frames:
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if frame is not None:
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@ -185,15 +197,13 @@ def main(ARGS):
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wav_data = bytearray()
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text = model.finishStream(stream_context)
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print("Recognized: %s" % text)
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stream_context = model.setupStream()
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stream_context = model.createStream()
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if __name__ == '__main__':
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BEAM_WIDTH = 500
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DEFAULT_SAMPLE_RATE = 16000
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LM_ALPHA = 0.75
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LM_BETA = 1.85
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N_FEATURES = 26
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N_CONTEXT = 9
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import argparse
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parser = argparse.ArgumentParser(description="Stream from microphone to DeepSpeech using VAD")
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@ -204,6 +214,8 @@ if __name__ == '__main__':
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help="Disable spinner")
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parser.add_argument('-w', '--savewav',
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help="Save .wav files of utterences to given directory")
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parser.add_argument('-f', '--file',
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help="Read from .wav file instead of microphone")
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parser.add_argument('-m', '--model', required=True,
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help="Path to the model (protocol buffer binary file, or entire directory containing all standard-named files for model)")
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@ -214,13 +226,9 @@ if __name__ == '__main__':
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parser.add_argument('-t', '--trie', default='trie',
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help="Path to the language model trie file created with native_client/generate_trie. Default: trie")
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parser.add_argument('-d', '--device', type=int, default=None,
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help="Device input index (Int) as listed by pyaudio.PyAudio.get_device_info_by_index(). If not provided, falls back to PyAudio.get_default_device()")
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help="Device input index (Int) as listed by pyaudio.PyAudio.get_device_info_by_index(). If not provided, falls back to PyAudio.get_default_device().")
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parser.add_argument('-r', '--rate', type=int, default=DEFAULT_SAMPLE_RATE,
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help=f"Input device sample rate. Default: {DEFAULT_SAMPLE_RATE}. Your device may require 44100.")
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parser.add_argument('-nf', '--n_features', type=int, default=N_FEATURES,
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help=f"Number of MFCC features to use. Default: {N_FEATURES}")
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parser.add_argument('-nc', '--n_context', type=int, default=N_CONTEXT,
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help=f"Size of the context window used for producing timesteps in the input vector. Default: {N_CONTEXT}")
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parser.add_argument('-la', '--lm_alpha', type=float, default=LM_ALPHA,
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help=f"The alpha hyperparameter of the CTC decoder. Language Model weight. Default: {LM_ALPHA}")
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parser.add_argument('-lb', '--lm_beta', type=float, default=LM_BETA,
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@ -1,5 +1,6 @@
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deepspeech~=0.4.1
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deepspeech~=0.6.0a5
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pyaudio~=0.2.11
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webrtcvad~=2.0.10
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halo~=0.0.18
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numpy~=1.15.1
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scipy~=1.1.0
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@ -0,0 +1,21 @@
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#!/bin/bash
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set -xe
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THIS=$(dirname "$0")
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pushd ${THIS}
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source ../tests.sh
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pip install --user $(get_python_wheel_url "$1")
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pip install --user -r requirements.txt
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pulseaudio &
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python mic_vad_streaming.py \
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--model $HOME/DeepSpeech/models/output_graph.pbmm \
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--alphabet $HOME/DeepSpeech/models/alphabet.txt \
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--lm $HOME/DeepSpeech/models/lm.binary \
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--trie $HOME/DeepSpeech/models/trie \
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--file $HOME/DeepSpeech/audio/2830-3980-0043.wav
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popd
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@ -6,19 +6,17 @@ const Duplex = require('stream').Duplex;
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const Wav = require('node-wav');
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const BEAM_WIDTH = 1024;
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const N_FEATURES = 26;
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const N_CONTEXT = 9;
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let modelPath = './models/output_graph.pbmm';
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let alphabetPath = './models/alphabet.txt';
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let model = new DeepSpeech.Model(modelPath, N_FEATURES, N_CONTEXT, alphabetPath, BEAM_WIDTH);
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let model = new DeepSpeech.Model(modelPath, alphabetPath, BEAM_WIDTH);
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const LM_ALPHA = 0.75;
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const LM_BETA = 1.85;
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let lmPath = './models/lm.binary';
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let triePath = './models/trie';
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model.enableDecoderWithLM(alphabetPath, lmPath, triePath, LM_ALPHA, LM_BETA);
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model.enableDecoderWithLM(lmPath, triePath, LM_ALPHA, LM_BETA);
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let audioFile = process.argv[2] || './audio/2830-3980-0043.wav';
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@ -8,7 +8,7 @@
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},
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"dependencies": {
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"argparse": "^1.0.10",
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"deepspeech": "^0.4.1",
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"deepspeech": "^0.6.0-alpha.5",
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"node-wav": "0.0.2",
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"sox-stream": "^2.0.3",
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"util": "^0.11.1"
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@ -0,0 +1,18 @@
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#!/bin/bash
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set -xe
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THIS=$(dirname "$0")
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pushd ${THIS}
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source ../tests.sh
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npm install $(get_npm_package_url)
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npm install
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ln -s $HOME/DeepSpeech/models models
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node index.js $HOME/DeepSpeech/audio/2830-3980-0043.wav
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node index.js $HOME/DeepSpeech/audio/8455-210777-0068.wav
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node index.js $HOME/DeepSpeech/audio/4507-16021-0012.wav
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popd
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@ -0,0 +1,23 @@
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#!/bin/bash
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set -xe
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THIS=$(dirname "$0")
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source ../../taskcluster/tc-tests-utils.sh
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DEP_TASK_ID=$(curl -s https://queue.taskcluster.net/v1/task/${TASK_ID} | python -c 'import json; import sys; print(" ".join(json.loads(sys.stdin.read())["dependencies"]));')
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get_python_wheel_url()
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{
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local this_python_version=$1
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extract_python_versions "${this_python_version}" "pyver" "pyver_pkg" "py_unicode_type" "pyconf" "pyalias"
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echo "$(get_python_pkg_url "${pyver_pkg}" "${py_unicode_type}" "deepspeech" https://queue.taskcluster.net/v1/task/${DEP_TASK_ID}/artifacts/public)"
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}
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get_npm_package_url()
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{
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echo "https://queue.taskcluster.net/v1/task/${DEP_TASK_ID}/artifacts/public/deepspeech-${DS_VERSION}.tgz"
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}
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@ -22,9 +22,9 @@ def main(args):
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parser.add_argument('--stream', required=False, action='store_true',
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help='To use deepspeech streaming interface')
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args = parser.parse_args()
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if args.stream is True and len(sys.argv[1:]) == 3:
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if args.stream is True:
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print("Opening mic for streaming")
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elif args.audio is not None and len(sys.argv[1:]) == 6:
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elif args.audio is not None:
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logging.debug("Transcribing audio file @ %s" % args.audio)
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else:
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parser.print_help()
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@ -72,7 +72,7 @@ def main(args):
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logging.debug("************************************************************************************************************")
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print("%-30s %-20.3f %-20.3f %-20.3f %-0.3f" % (filename + ext, audio_length, inference_time, model_retval[1], model_retval[2]))
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else:
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sctx = model_retval[0].setupStream()
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sctx = model_retval[0].createStream()
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subproc = subprocess.Popen(shlex.split('rec -q -V0 -e signed -L -c 1 -b 16 -r 16k -t raw - gain -2'),
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stdout=subprocess.PIPE,
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bufsize=0)
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@ -283,7 +283,7 @@ class App(QMainWindow):
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logging.debug("Start Recording pressed")
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logging.debug("Preparing for transcription...")
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sctx = self.model[0].setupStream()
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sctx = self.model[0].createStream()
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subproc = subprocess.Popen(shlex.split('rec -q -V0 -e signed -L -c 1 -b 16 -r 16k -t raw - gain -2'),
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stdout=subprocess.PIPE,
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bufsize=0)
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|
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@ -1,3 +1,3 @@
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deepspeech==0.4.1
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deepspeech~=0.6.0a5
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webrtcvad
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pyqt5
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@ -0,0 +1,23 @@
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#!/bin/bash
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set -xe
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THIS=$(dirname "$0")
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pushd ${THIS}
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source ../tests.sh
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pip install --user $(get_python_wheel_url "$1")
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pip install --user -r requirements.txt
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python audioTranscript_cmd.py \
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--audio $HOME/DeepSpeech/audio/2830-3980-0043.wav \
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--aggressive 0 \
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--model $HOME/DeepSpeech/models/
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python audioTranscript_cmd.py \
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--audio $HOME/DeepSpeech/audio/2830-3980-0043.wav \
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--aggressive 0 \
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--model $HOME/DeepSpeech/models/ \
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--stream
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popd
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@ -16,19 +16,17 @@ Load the pre-trained model into the memory
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Returns a list [DeepSpeech Object, Model Load Time, LM Load Time]
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'''
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def load_model(models, alphabet, lm, trie):
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N_FEATURES = 26
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N_CONTEXT = 9
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BEAM_WIDTH = 500
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LM_ALPHA = 0.75
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LM_BETA = 1.85
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model_load_start = timer()
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ds = Model(models, N_FEATURES, N_CONTEXT, alphabet, BEAM_WIDTH)
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ds = Model(models, alphabet, BEAM_WIDTH)
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model_load_end = timer() - model_load_start
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logging.debug("Loaded model in %0.3fs." % (model_load_end))
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lm_load_start = timer()
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ds.enableDecoderWithLM(alphabet, lm, trie, LM_ALPHA, LM_BETA)
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ds.enableDecoderWithLM(lm, trie, LM_ALPHA, LM_BETA)
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lm_load_end = timer() - lm_load_start
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logging.debug('Loaded language model in %0.3fs.' % (lm_load_end))
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|
|
|||
|
|
@ -0,0 +1,61 @@
|
|||
$if: '(event.event != "push") && (event.event != "tag")'
|
||||
then:
|
||||
taskId: ${taskcluster.taskId}
|
||||
provisionerId: ${taskcluster.docker.provisionerId}
|
||||
workerType: ${taskcluster.docker.workerType}
|
||||
taskGroupId: ${taskcluster.taskGroupId}
|
||||
schedulerId: ${taskcluster.schedulerId}
|
||||
dependencies:
|
||||
$map: { $eval: build.dependencies }
|
||||
each(b):
|
||||
$eval: as_slugid(b)
|
||||
created: { $fromNow: '0 sec' }
|
||||
deadline: { $fromNow: '1 day' }
|
||||
expires: { $fromNow: '7 days' }
|
||||
|
||||
extra:
|
||||
github:
|
||||
{ $eval: taskcluster.github_events.pull_request }
|
||||
|
||||
routes:
|
||||
- "notify.irc-channel.${notifications.irc}.on-exception"
|
||||
- "notify.irc-channel.${notifications.irc}.on-failed"
|
||||
|
||||
scopes: [
|
||||
"queue:route:notify.irc-channel.*"
|
||||
]
|
||||
|
||||
payload:
|
||||
maxRunTime: { $eval: to_int(build.maxRunTime) }
|
||||
image: ${build.docker_image}
|
||||
|
||||
env:
|
||||
DEEPSPEECH_MODEL: "https://github.com/lissyx/DeepSpeech/releases/download/tc-0.6.0/models.tar.gz"
|
||||
DEEPSPEECH_AUDIO: "https://github.com/mozilla/DeepSpeech/releases/download/v0.4.1/audio-0.4.1.tar.gz"
|
||||
PIP_DEFAULT_TIMEOUT: "60"
|
||||
|
||||
command:
|
||||
- "/bin/bash"
|
||||
- "--login"
|
||||
- "-cxe"
|
||||
- $let:
|
||||
extraSystemSetup: { $eval: strip(str(build.system_setup)) }
|
||||
in: >
|
||||
apt-get -qq update && apt-get -qq -y upgrade && apt-get -qq -y install git sox sudo && ${extraSystemSetup} &&
|
||||
adduser --system --home ${system.homedir.linux} ${system.username} &&
|
||||
cd ${system.homedir.linux} &&
|
||||
echo -e "#!/bin/bash\nset -xe\n env && id && mkdir ~/DeepSpeech/ && git clone --quiet ${event.head.repo.url} ~/DeepSpeech/ds/ && cd ~/DeepSpeech/ds && git checkout --quiet ${event.head.sha} && wget -O - $DEEPSPEECH_MODEL | tar -C ~/DeepSpeech/ -xzvf - && wget -O - $DEEPSPEECH_AUDIO | tar -C ~/DeepSpeech/ -xzvf - " > /tmp/clone.sh && chmod +x /tmp/clone.sh &&
|
||||
sudo -H -u ${system.username} /bin/bash /tmp/clone.sh &&
|
||||
sudo -H -u ${system.username} --preserve-env /bin/bash ${build.args.tests_cmdline}
|
||||
|
||||
artifacts:
|
||||
"public":
|
||||
type: "directory"
|
||||
path: "/tmp/artifacts/"
|
||||
expires: { $fromNow: '7 days' }
|
||||
|
||||
metadata:
|
||||
name: ${build.metadata.name}
|
||||
description: ${build.metadata.description}
|
||||
owner: ${event.head.user.email}
|
||||
source: ${event.head.repo.url}
|
||||
|
|
@ -0,0 +1,13 @@
|
|||
build:
|
||||
template_file: examples-base.tyml
|
||||
docker_image: "node:10"
|
||||
dependencies:
|
||||
- "node-package-cpu"
|
||||
system_setup:
|
||||
>
|
||||
apt-get -qq -y install ffmpeg
|
||||
args:
|
||||
tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/examples/ffmpeg_vad_streaming/test.sh"
|
||||
metadata:
|
||||
name: "DeepSpeech examples: ffmpeg VAD Streaming NodeJS v10.x"
|
||||
description: "DeepSpeech examples: ffmpeg VAD Streaming NodeJS v10.x"
|
||||
|
|
@ -0,0 +1,13 @@
|
|||
build:
|
||||
template_file: examples-base.tyml
|
||||
docker_image: "node:8"
|
||||
dependencies:
|
||||
- "node-package-cpu"
|
||||
system_setup:
|
||||
>
|
||||
apt-get -qq -y install ffmpeg
|
||||
args:
|
||||
tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/examples/ffmpeg_vad_streaming/test.sh"
|
||||
metadata:
|
||||
name: "DeepSpeech examples: ffmpeg VAD Streaming NodeJS v8.x"
|
||||
description: "DeepSpeech examples: ffmpeg VAD Streaming NodeJS v8.x"
|
||||
|
|
@ -0,0 +1,13 @@
|
|||
build:
|
||||
template_file: examples-base.tyml
|
||||
docker_image: "python:3.6"
|
||||
dependencies:
|
||||
- "linux-amd64-cpu-opt"
|
||||
system_setup:
|
||||
>
|
||||
apt-get -qq -y install portaudio19-dev pulseaudio
|
||||
args:
|
||||
tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/examples/mic_vad_streaming/test.sh 3.6.0:m"
|
||||
metadata:
|
||||
name: "DeepSpeech examples: mic VAD streaming Py3.6"
|
||||
description: "DeepSpeech examples: mic VAD streaming Python 3.6"
|
||||
|
|
@ -0,0 +1,13 @@
|
|||
build:
|
||||
template_file: examples-base.tyml
|
||||
docker_image: "python:3.7"
|
||||
dependencies:
|
||||
- "linux-amd64-cpu-opt"
|
||||
system_setup:
|
||||
>
|
||||
apt-get -qq -y install portaudio19-dev pulseaudio
|
||||
args:
|
||||
tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/examples/mic_vad_streaming/test.sh 3.7.0:m"
|
||||
metadata:
|
||||
name: "DeepSpeech examples: mic VAD streaming Py3.7"
|
||||
description: "DeepSpeech examples: mic VAD streaming Python 3.7"
|
||||
|
|
@ -0,0 +1,10 @@
|
|||
build:
|
||||
template_file: examples-base.tyml
|
||||
docker_image: "node:10"
|
||||
dependencies:
|
||||
- "node-package-cpu"
|
||||
args:
|
||||
tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/examples/nodejs_wav/test.sh"
|
||||
metadata:
|
||||
name: "DeepSpeech examples: NodeJS WAV NodeJS v10.x"
|
||||
description: "DeepSpeech examples: NodeJS WAV NodeJS v10.x"
|
||||
|
|
@ -0,0 +1,10 @@
|
|||
build:
|
||||
template_file: examples-base.tyml
|
||||
docker_image: "node:8"
|
||||
dependencies:
|
||||
- "node-package-cpu"
|
||||
args:
|
||||
tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/examples/nodejs_wav/test.sh"
|
||||
metadata:
|
||||
name: "DeepSpeech examples: NodeJS WAV NodeJS v8.x"
|
||||
description: "DeepSpeech examples: NodeJS WAV NodeJS v8.x"
|
||||
|
|
@ -0,0 +1,10 @@
|
|||
build:
|
||||
template_file: examples-base.tyml
|
||||
docker_image: "python:3.5"
|
||||
dependencies:
|
||||
- "linux-amd64-cpu-opt"
|
||||
args:
|
||||
tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/examples/vad_transcriber/test.sh 3.5.0:m"
|
||||
metadata:
|
||||
name: "DeepSpeech examples: VAD transcriber Py3.5"
|
||||
description: "DeepSpeech examples: VAD transcriberaming Python 3.5"
|
||||
|
|
@ -0,0 +1,10 @@
|
|||
build:
|
||||
template_file: examples-base.tyml
|
||||
docker_image: "python:3.6"
|
||||
dependencies:
|
||||
- "linux-amd64-cpu-opt"
|
||||
args:
|
||||
tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/examples/vad_transcriber/test.sh 3.6.0:m"
|
||||
metadata:
|
||||
name: "DeepSpeech examples: VAD transcriber Py3.6"
|
||||
description: "DeepSpeech examples: VAD transcriberaming Python 3.6"
|
||||
|
|
@ -0,0 +1,10 @@
|
|||
build:
|
||||
template_file: examples-base.tyml
|
||||
docker_image: "python:3.7"
|
||||
dependencies:
|
||||
- "linux-amd64-cpu-opt"
|
||||
args:
|
||||
tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/examples/vad_transcriber/test.sh 3.7.0:m"
|
||||
metadata:
|
||||
name: "DeepSpeech examples: VAD transcriber Py3.7"
|
||||
description: "DeepSpeech examples: VAD transcriberaming Python 3.7"
|
||||
Loading…
Reference in New Issue