File size: 6,261 Bytes
7f9420f
0b78698
7f9420f
 
 
 
 
 
 
0b78698
7f9420f
0b78698
7f9420f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0b78698
7f9420f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
567e4b2
339629e
 
 
 
 
 
 
 
 
 
 
 
7f9420f
 
 
f16f614
7f9420f
f16f614
7f9420f
f16f614
7f9420f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f16f614
 
7f9420f
 
 
 
 
f16f614
7f9420f
 
 
 
 
 
 
 
 
f16f614
7f9420f
 
f16f614
7f9420f
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
import spaces
import gradio as gr
import io
import os
import re
import torch
import torchaudio
from pathlib import Path
from whisperspeech.pipeline import Pipeline

DEVEL=os.environ.get('DEVEL', False)

title = """
<picture>
  <source srcset="https://huggingface.co/spaces/collabora/whisperspeech/resolve/main/dark-banner.png" media="(prefers-color-scheme: dark)" />
  <img alt="WhisperSpeech banner with Collabora and LAION logos" src="https://huggingface.co/spaces/collabora/whisperspeech/resolve/main/light-banner.png" style="width: 60%; margin: 0 auto;" />
</picture>
# Welcome to Collabora's WhisperSpeech
WhisperSpeech is an Open Source text-to-speech system built by Collabora and LAION by inverting Whisper.
The model is fully open and you can run it on your local hardware. It's like **Stable Diffusion but for speech**
– both powerful and easily customizable.
[You can contribute to WhisperSpeech on Github.](https://github.com/collabora/WhisperSpeech)
You can also join the discussion on Discord [![](https://dcbadge.vercel.app/api/server/FANw4rHD5E)](https://discord.gg/FANw4rHD5E)
Huge thanks to [Tonic](https://huggingface.co/Tonic) who helped build this Space for WhisperSpeech.
### How to Use It
Write you text in the box, you can use language tags (`<en>` or `<pl>`) to create multilingual speech.
Optionally you can upload a speech sample or give it a file URL to clone an existing voice. Check out the
examples at the bottom of the page for inspiration.
"""

footer = """
### How to use it locally
```
pip install -U WhisperSpeech
```
Afterwards:
```
from whisperspeech.pipeline import Pipeline
pipe = Pipeline(torch_compile=True)
pipe.generate_to_file("output.wav", "Hello from WhisperSpeech.")
```
"""


text_examples = [
    ["This is the first demo of Whisper Speech, a fully open source text-to-speech model trained by Collabora and Lion on the Juwels supercomputer.", None],
    ["World War II or the Second World War was a global conflict that lasted from 1939 to 1945. The vast majority of the world's countries, including all the great powers, fought as part of two opposing military alliances: the Allies and the Axis.", "https://upload.wikimedia.org/wikipedia/commons/7/75/Winston_Churchill_-_Be_Ye_Men_of_Valour.ogg"],
    ["<pl>To jest pierwszy test wielojęzycznego <en>Whisper Speech <pl>, modelu zamieniającego tekst na mowę, który Collabora i Laion nauczyli na superkomputerze <en>Jewels.", None],
    ["<en> WhisperSpeech is an Open Source library that helps you convert text to speech. <pl>Teraz także po Polsku! <en>I think I just tried saying \"now also in Polish\", don't judge me...", None],
    # ["<de> WhisperSpeech is multi-lingual <es> y puede cambiar de idioma <hi> मध्य वाक्य में"],
    ["<pl>To jest pierwszy test naszego modelu. Pozdrawiamy serdecznie.", None],
    # ["<en> The big difference between Europe <fr> et les Etats Unis <pl> jest to, że mamy tak wiele języków <uk> тут, в Європі"]
]

def parse_multilingual_text(input_text):
    pattern = r"(?:<(\w+)>)|([^<]+)"
    cur_lang = 'en'
    segments = []
    for i, (lang, txt) in enumerate(re.findall(pattern, input_text)):
        if lang: cur_lang = lang
        else: segments.append((cur_lang, f"  {txt}  ")) # add spaces to give it some time to switch languages
    if not segments: return [("en", "")]
    return segments

#@spaces.GPU(enable_queue=True)
def generate_audio(pipe, segments, speaker, speaker_url, cps=14):
    if isinstance(speaker, (str, Path)): speaker = pipe.extract_spk_emb(speaker)
    elif speaker_url: speaker = pipe.extract_spk_emb(speaker_url)
    else: speaker = pipe.default_speaker
    langs, texts = [list(x) for x in zip(*segments)]
    print(texts, langs)
    stoks = pipe.t2s.generate(texts, cps=cps, lang=langs)
    stoks = stoks[stoks!=512]
    atoks = pipe.s2a.generate(stoks, speaker.unsqueeze(0))
    audio = pipe.vocoder.decode(atoks)
    return audio.cpu()

def whisper_speech_demo(multilingual_text, speaker_audio=None, speaker_url="", cps=14):
    if len(multilingual_text) == 0:
        raise gr.Error("Please enter some text for me to speak!")

    segments = parse_multilingual_text(multilingual_text)

    audio = generate_audio(pipe, segments, speaker_audio, speaker_url, cps)

    return (24000, audio.T.numpy())

    # Did not work for me in Safari:
    # mp3 = io.BytesIO()
    # torchaudio.save(mp3, audio, 24000, format='mp3')
    # return mp3.getvalue()

pipe = Pipeline(torch_compile=not DEVEL)
# warmup will come from regenerating the examples

with gr.Blocks() as demo:
    gr.Markdown(title)
    with gr.Row(equal_height=True):
        with gr.Column(scale=2):
            
            text_input = gr.Textbox(label="Enter multilingual text💬📝",
                                    value=text_examples[0][0],
                                    info="You can use `<en>` for English and `<pl>` for Polish, see examples below.")
            
            cps = gr.Slider(value=14, minimum=10, maximum=15, step=.25,
                            label="Tempo (in characters per second)")
            
            
            with gr.Row(equal_height=True):
                speaker_input = gr.Audio(label="Upload or Record Speaker Audio (optional)🌬️💬", 
                                     sources=["upload", "microphone"],
                                     type='filepath')
                url_input = gr.Textbox(label="alternatively, you can paste in an audio file URL:")
            gr.Markdown("  \n  ") # fixes the bottom overflow from Audio
            generate_button = gr.Button("Try Collabora's WhisperSpeech🌟")
        with gr.Column(scale=1):
            output_audio = gr.Audio(label="WhisperSpeech says…")

    with gr.Column():
        gr.Markdown("### Try these examples to get started !🌟🌬️")
        gr.Examples(
            examples=text_examples,
            inputs=[text_input, url_input],
            outputs=[output_audio],
            fn=whisper_speech_demo,
            cache_examples=not DEVEL,
        )

    generate_button.click(whisper_speech_demo, inputs=[text_input, speaker_input, url_input, cps], outputs=output_audio)
    gr.Markdown(footer)

demo.launch(server_port=3000 if DEVEL else None)