@@ -30,17 +30,25 @@ Extra pretrained models
3030Note that the following models are not explained in our book.
3131Those were trained using extra recipes found in our GitHub repository.
3232
33- +----------------------------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
34- | Model ID | Class | Details of the model |
35- +----------------------------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
36- | ``tacotron2_pwg_jsut16k `` | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Tacotron 2 with Parallel WaveGAN (PWG). Trained on JSUT corpus. Sampling rate: 16 kHz. |
37- +----------------------------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
38- | ``tacotron2_pwg_jsut24k `` | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Tacotron 2 with Parallel WaveGAN (PWG). Trained on JSUT corpus. Sampling rate: 24 kHz. |
39- +----------------------------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
40- | ``multspk_tacotron2_pwg_jvs16k `` | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Multi-speaker Tacotron 2 with Parallel WaveGAN (PWG). Trained on JVS corpus. Sampling rate: 16 kHz. |
41- +----------------------------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
42- | ``multspk_tacotron2_pwg_jvs24k `` | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Multi-speaker Tacotron 2 with Parallel WaveGAN (PWG). Trained on JVS corpus. Sampling rate: 24 kHz. |
43- +----------------------------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
33+ +--------------------------------------+--------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
34+ | Model ID | Corpus | Class | Details of the model |
35+ +--------------------------------------+--------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
36+ | ``tacotron2_pwg_jsut16k `` | JSUT | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Tacotron 2 with Parallel WaveGAN (PWG). Trained on JSUT corpus. Sampling rate: 16 kHz. |
37+ +--------------------------------------+--------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
38+ | ``tacotron2_pwg_jsut24k `` | JSUT | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Tacotron 2 with PWG. Trained on JSUT corpus. Sampling rate: 24 kHz. |
39+ +--------------------------------------+--------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
40+ | ``tacotron2_hifipwg_jsut24k `` | JSUT | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Tacotron 2 with HiFi-GAN. Trained on JSUT corpus. Sampling rate: 24 kHz. |
41+ +--------------------------------------+--------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
42+ | ``multspk_tacotron2_pwg_jvs16k `` | JVS | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Multi-speaker Tacotron 2 with PWG. Trained on JVS corpus. Sampling rate: 16 kHz. |
43+ +--------------------------------------+--------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
44+ | ``multspk_tacotron2_pwg_jvs24k `` | JVS | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Multi-speaker Tacotron 2 with Parallel WaveGAN (PWG). Trained on JVS corpus. Sampling rate: 24 kHz. |
45+ +--------------------------------------+--------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
46+ | ``multspk_tacotron2_hifipwg_jvs24k `` | JVS | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Multi-speaker Tacotron 2 with HiFi-GAN. Trained on JVS corpus. Sampling rate: 24 kHz. |
47+ +--------------------------------------+--------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
48+ | ``multspk_tacotron2_pwg_cv16k `` | common voice | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Multi-speaker Tacotron 2 with PWG. Trained on common voice (ja) corpus. Sampling rate: 16 kHz. |
49+ +--------------------------------------+--------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
50+ | ``multspk_tacotron2_pwg_cv24k `` | common voice | :py:class: `ttslearn.contrib.tacotron2_pwg.Tacotron2PWGTTS ` | Multi-speaker Tacotron 2 with PWG. Trained on common voice (ja) corpus. Sampling rate: 24 kHz. |
51+ +--------------------------------------+--------------+------------------------------------------------------------+-----------------------------------------------------------------------------------------------------+
4452
4553Helpers
4654--------
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