From ffd0238a16461079fd9464a4dbda85e7144fd1c6 Mon Sep 17 00:00:00 2001 From: James Betker Date: Fri, 6 May 2022 00:11:10 -0600 Subject: [PATCH] v2.2 --- README.md | 13 +++-- examples/prompting/angry.mp3 | Bin 0 -> 7629 bytes examples/prompting/happy.mp3 | Bin 0 -> 8301 bytes examples/prompting/sad.mp3 | Bin 0 -> 6285 bytes examples/prompting/scared.mp3 | Bin 0 -> 6861 bytes examples/various/desktop.ini | 4 -- setup.py | 2 +- tortoise/models/vocoder.py | 2 - tortoise/utils/audio.py | 2 +- tortoise/utils/wav2vec_alignment.py | 7 ++- tortoise/voices/applejack/1.wav | Bin 0 -> 327614 bytes tortoise/voices/applejack/2.wav | Bin 0 -> 331262 bytes tortoise/voices/applejack/3.wav | Bin 0 -> 326548 bytes tortoise/voices/rainbow/1.wav | Bin 0 -> 319782 bytes tortoise/voices/rainbow/2.wav | Bin 0 -> 286256 bytes tortoise/voices/rainbow/3.wav | Bin 0 -> 288266 bytes tortoise/voices/train_daws/1.mp3 | Bin 0 -> 36067 bytes tortoise/voices/train_daws/2.mp3 | Bin 0 -> 35336 bytes tortoise/voices/train_daws/3.mp3 | Bin 0 -> 35649 bytes tortoise/voices/train_dreams/1.mp3 | Bin 0 -> 33664 bytes tortoise/voices/train_dreams/2.mp3 | Bin 0 -> 33246 bytes tortoise/voices/train_dreams/3.mp3 | Bin 0 -> 34082 bytes tortoise/voices/train_empire/1.mp3 | Bin 0 -> 27708 bytes tortoise/voices/train_empire/2.mp3 | Bin 0 -> 30111 bytes tortoise/voices/train_empire/3.mp3 | Bin 0 -> 28126 bytes tortoise/voices/train_mouse/1.mp3 | Bin 0 -> 19244 bytes tortoise/voices/train_mouse/2.mp3 | Bin 0 -> 13706 bytes tortoise/voices/train_mouse/3.mp3 | Bin 0 -> 13706 bytes tortoise/voices/yannic/00045.mp3 | Bin 0 -> 151737 bytes tortoise/voices/yannic/00055.mp3 | Bin 0 -> 148602 bytes tortoise/voices/yannic/00203.mp3 | Bin 0 -> 157379 bytes tortoise_v2_examples.html | 81 +++++++++++++++++++++------- 32 files changed, 77 insertions(+), 34 deletions(-) create mode 100644 examples/prompting/angry.mp3 create mode 100644 examples/prompting/happy.mp3 create mode 100644 examples/prompting/sad.mp3 create mode 100644 examples/prompting/scared.mp3 delete mode 100644 examples/various/desktop.ini create mode 100644 tortoise/voices/applejack/1.wav create mode 100644 tortoise/voices/applejack/2.wav create mode 100644 tortoise/voices/applejack/3.wav create mode 100644 tortoise/voices/rainbow/1.wav create mode 100644 tortoise/voices/rainbow/2.wav create mode 100644 tortoise/voices/rainbow/3.wav create mode 100644 tortoise/voices/train_daws/1.mp3 create mode 100644 tortoise/voices/train_daws/2.mp3 create mode 100644 tortoise/voices/train_daws/3.mp3 create mode 100644 tortoise/voices/train_dreams/1.mp3 create mode 100644 tortoise/voices/train_dreams/2.mp3 create mode 100644 tortoise/voices/train_dreams/3.mp3 create mode 100644 tortoise/voices/train_empire/1.mp3 create mode 100644 tortoise/voices/train_empire/2.mp3 create mode 100644 tortoise/voices/train_empire/3.mp3 create mode 100644 tortoise/voices/train_mouse/1.mp3 create mode 100644 tortoise/voices/train_mouse/2.mp3 create mode 100644 tortoise/voices/train_mouse/3.mp3 create mode 100644 tortoise/voices/yannic/00045.mp3 create mode 100644 tortoise/voices/yannic/00055.mp3 create mode 100644 tortoise/voices/yannic/00203.mp3 diff --git a/README.md b/README.md index 15f8d32..ecf8968 100644 --- a/README.md +++ b/README.md @@ -9,6 +9,11 @@ This repo contains all the code needed to run Tortoise TTS in inference mode. ### New features +#### v2.2; 2022/5/5 +- Added several new voices from the training set. +- Automated redaction. Wrap the text you want to use to prompt the model but not be spoken in brackets. +- Bug fixes + #### v2.1; 2022/5/2 - Added ability to produce totally random voices. - Added ability to download voice conditioning latent via a script, and then use a user-provided conditioning latent. @@ -95,11 +100,9 @@ For the those in the ML space: this is created by projecting a random vector ont ### Provided voices -This repo comes with several pre-packaged voices. You will be familiar with many of them. :) - -Most of the provided voices were not found in the training set. Experimentally, it seems that voices from the training set -produce more realistic outputs then those outside of the training set. Any voice prepended with "train" came from the -training set. +This repo comes with several pre-packaged voices. Voices prepended with "train_" came from the training set and perform +far better than the others. If your goal is high quality speech, I recommend you pick one of them. 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description="A high quality multi-voice text-to-speech library", diff --git a/tortoise/models/vocoder.py b/tortoise/models/vocoder.py index d38fb56..346f381 100644 --- a/tortoise/models/vocoder.py +++ b/tortoise/models/vocoder.py @@ -284,8 +284,6 @@ class UnivNetGenerator(nn.Module): self.remove_weight_norm() def remove_weight_norm(self): - print('Removing weight norm...') - nn.utils.remove_weight_norm(self.conv_pre) for layer in self.conv_post: diff --git a/tortoise/utils/audio.py b/tortoise/utils/audio.py index e402910..f68e831 100644 --- a/tortoise/utils/audio.py +++ b/tortoise/utils/audio.py @@ -137,7 +137,7 @@ class TacotronSTFT(torch.nn.Module): self.stft_fn = STFT(filter_length, hop_length, win_length) from librosa.filters import mel as librosa_mel_fn mel_basis = librosa_mel_fn( - sampling_rate, filter_length, n_mel_channels, mel_fmin, mel_fmax) + sr=sampling_rate, n_fft=filter_length, n_mels=n_mel_channels, fmin=mel_fmin, fmax=mel_fmax) mel_basis = torch.from_numpy(mel_basis).float() self.register_buffer('mel_basis', mel_basis) diff --git a/tortoise/utils/wav2vec_alignment.py b/tortoise/utils/wav2vec_alignment.py index fe4a3fb..4a05659 100644 --- a/tortoise/utils/wav2vec_alignment.py +++ b/tortoise/utils/wav2vec_alignment.py @@ -66,7 +66,7 @@ class Wav2VecAlignment: logits = logits[0] pred_string = self.tokenizer.decode(logits.argmax(-1).tolist()) - fixed_expectation = max_alignment(expected_text, pred_string) + fixed_expectation = max_alignment(expected_text.lower(), pred_string) w2v_compression = orig_len // logits.shape[0] expected_tokens = self.tokenizer.encode(fixed_expectation) expected_chars = list(fixed_expectation) @@ -100,7 +100,10 @@ class Wav2VecAlignment: break pop_till_you_win() - assert len(expected_tokens) == 0, "This shouldn't happen. My coding sucks." + if not (len(expected_tokens) == 0 and len(alignments) == len(expected_text)): + torch.save([audio, expected_text], 'alignment_debug.pth') + assert False, "Something went wrong with the alignment algorithm. I've dumped a file, 'alignment_debug.pth' to" \ + "your current working directory. Please report this along with the file so it can get fixed." # Now fix up alignments. 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b/tortoise_v2_examples.html @@ -1,4 +1,16 @@ -These words were never spoken.

Handpicked results


+TorToiSe - These words were never spoken. + +

Introduction 🐢

+
+ +

This page demonstrates some of the results of TorToiSe.

+ +

Handpicked results 🐢

+

Following are several particularly good results generated by the model.

+ +

Short-form

+



@@ -16,14 +28,28 @@


-

Handpicked longform result:


-

Compared to Tacotron2 (with the LJSpeech voice):

Tacotron2+WaveglowTorToiSe

+ +

Short-form

+
+ +

Compared to Tacotron2 (with the LJSpeech voice): 🐢

+

LJSpeech is a popular dataset used to train small-scale TTS models. TorToiSe is a multi-voice model, following is how +it renders the LJSpeech voice with no fine-tuning, compared with results for the same text from the popular Tacotron2 +model paired with the Waveglow transformer:

+
Tacotron2+WaveglowTorToiSe






-

Various spoken texts for all voices:

+
textangiedanieldeniroemmafreemangeralthallejlawljmyselfpatsnakestomtrain_atkinstrain_dotricetrain_kennardweaverwilliam
+ +

All Results 🐢

+

Following are all the results from which the hand-picked results were drawn from. Also included is the reference + audio that the program is trying to mimic. This will give you a better sense of how TorToiSe really performs.

+ +

Short-form

+ @@ -44,19 +70,36 @@ -
textangiedanieldeniroemmafreemangeralthallejlawljmyselfpatsnakestomtrain_atkinstrain_dotricetrain_kennardweaverwilliam
reference clip
autoregressive_ml
bengio_it_needs_to_know_what_is_bad
tacotron2_sample3
tacotron2_sample4
watts_this_is_the_real_secret_of_life
wilde_nowadays_people_know_the_price

Longform result for all voices:


-
-
-
-
-
-
-
-
-
-
-
-
-
-
+
wilde_nowadays_people_know_the_price
+ +

Long-form

+Angelina:
+Craig:
+Deniro:
+Emma:
+Freeman:
+Geralt:
+Halle:
+Jlaw:
+LJ:
+Myself:
+Pat:
+Snakes:
+Tom:
+Weaver:
+William:
+ +

Prompt Engineering 🐢

+

Tortoise is capable of "prompt-engineering" in that tone and prosody is affected by the emotions inflected in the words +fed to the program. For example, prompting the model with "[I am so angry,] I went to the park and threw a ball" will +result in it outputting "I went to the park and threw the ball" with an angry tone.

+ +

Following are a few examples of different prompts. The effect is subtle, but is definitely there. Many voices are +less effected by this.

+ +Angry:
+Sad:
+Happy:
+Scared:
+ \ No newline at end of file

TorToiSe is a text-to-speech program built in April 2022 by jbetker@. TorToiSe is open source, with trained model weights +available at https://github.com/neonbjb/tortoise-tts