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Josh Meyer 2021-09-15 07:57:53 -04:00
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notebooks/train_your_first_coqui_STT_model.ipynb
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@ -54,9 +54,9 @@
"2. the **size** of that audio file\n",
"3. the **transcript** of that audio file.\n",
"\n",
"Formatting the audio and transcript isn't too difficult in this case. We define a custom data importer called `download_sample_data()` which does all the work. If you have a custom dataset, you will probably want to write a custom data importer.\n",
"Formatting the audio and transcript isn't too difficult in this case. We define `download_sample_data()` which does all the work. If you have a custom dataset, you will want to write a custom data importer.\n",
"\n",
"**Second things second**: we want an alphabet. The output layer of a typical* 🐸 STT model represents letters in the alphabet, and you should specify this alphabet before training. Let's download an English alphabet from Coqui and use that.\n",
"**Second things second**: we want an alphabet. The output layer of a typical* 🐸 STT model represents letters in the alphabet. Let's download an English alphabet from Coqui and use that.\n",
"\n",
"*_If you are working with languages with large character sets (e.g. Chinese), you can set `bytes_output_mode=True` instead of supplying an `alphabet.txt` file. In this case, the output layer of the STT model will correspond to individual UTF-8 bytes instead of individual characters._"
]
@ -98,7 +98,7 @@
"id": "96e8b708",
"metadata": {},
"source": [
"### Take a look at the data (*Optional* )"
"### 👀 Take a look at the data"
]
},
{
@ -150,7 +150,7 @@
" dev_files=[\"english/ldc93s1.csv\"],\n",
" test_files=[\"english/ldc93s1.csv\"],\n",
" load_train=\"init\",\n",
" n_hidden=100,\n",
" n_hidden=200,\n",
" epochs=100,\n",
")"
]
@ -160,7 +160,7 @@
"id": "799c1425",
"metadata": {},
"source": [
"### View all Config settings (*Optional*) "
"### 👀 View all Config settings"
]
},
{