Add importer for English subset of Multilingual LibriSpeech

bin/import_mls_english.py

@@ -0,0 +1,96 @@
+#!/usr/bin/env python
+import argparse
+import ctypes
+import os
+
+import pandas
+
+from pathlib import Path
+from tqdm import tqdm
+
+
+def read_ogg_opus_duration(ogg_file_path):
+    error = ctypes.c_int()
+    opusfile = pyogg.opus.op_open_file(
+        ogg_file_path.encode("utf-8"), ctypes.pointer(error)
+    )
+
+    if error.value != 0:
+        raise ValueError(
+            ("Ogg/Opus file could not be read." "Error code: {}").format(error.value)
+        )
+
+    pcm_buffer_size = pyogg.opus.op_pcm_total(opusfile, -1)
+    channel_count = pyogg.opus.op_channel_count(opusfile, -1)
+    sample_rate = 48000  # opus files are always 48kHz
+    sample_width = 2  # always 16-bit
+    pyogg.opus.op_free(opusfile)
+    return pcm_buffer_size / sample_rate
+
+
+def main(root_dir):
+    for subset in ("test",):
+        print("Processing {} subset...".format(subset))
+        with open(Path(root_dir) / subset / "transcripts.txt") as fin:
+            subset_entries = []
+            for i, line in tqdm(enumerate(fin)):
+                audio_id, transcript = line.split("\t")
+                audio_id_parts = audio_id.split("_")
+                # e.g. 4800_10003_000000 -> train/audio/4800/10003/4800_10003_000000.opus
+                audio_path = (
+                    Path(root_dir)
+                    / subset
+                    / "audio"
+                    / audio_id_parts[0]
+                    / audio_id_parts[1]
+                    / "{}.opus".format(audio_id)
+                )
+                audio_filesize = os.path.getsize(audio_path)
+                # TODO: support other languages
+                transcript = (
+                    transcript.strip()
+                    .replace("-", " ")
+                    .replace("ñ", "n")
+                    .replace(".", "")
+                    .translate(
+                        {
+                            ord(ch): None
+                            for ch in (
+                                "а",
+                                "в",
+                                "е",
+                                "и",
+                                "к",
+                                "м",
+                                "н",
+                                "о",
+                                "п",
+                                "р",
+                                "т",
+                                "ы",
+                                "я",
+                            )
+                        }
+                    )
+                )
+                subset_entries.append(
+                    (
+                        audio_path.relative_to(root_dir),
+                        audio_filesize,
+                        transcript.strip(),
+                    )
+                )
+            df = pandas.DataFrame(
+                columns=["wav_filename", "wav_filesize", "transcript"],
+                data=subset_entries,
+            )
+            csv_name = Path(root_dir) / "{}.csv".format(subset)
+            df.to_csv(csv_name, index=False)
+            print("Wrote {}".format(csv_name))
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("root_dir", help="Path to the mls_english_opus directory.")
+    args = parser.parse_args()
+    main(args.root_dir)