File size: 7,990 Bytes
8fb8950
 
 
 
 
 
 
 
c105fbb
a71e647
 
 
 
 
c105fbb
 
8fb8950
 
 
 
 
 
 
 
 
 
 
 
 
a71e647
 
8fb8950
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a71e647
 
 
8fb8950
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a71e647
 
8fb8950
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c105fbb
 
 
 
 
a71e647
 
 
c105fbb
 
8fb8950
 
 
 
a71e647
 
 
c105fbb
 
 
 
 
 
a71e647
 
 
8fb8950
c105fbb
8fb8950
 
 
 
a71e647
 
 
8fb8950
 
 
 
 
 
a71e647
 
 
8fb8950
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a71e647
 
8fb8950
 
 
 
a71e647
 
8fb8950
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
import os

import gradio as gr
import numpy as np
import torch
import torchaudio
from seamless_communication.models.inference.translator import Translator

from lang_list import (
    LANGUAGE_NAME_TO_CODE,
    S2ST_TARGET_LANGUAGE_NAMES,
    S2TT_TARGET_LANGUAGE_NAMES,
    T2TT_TARGET_LANGUAGE_NAMES,
    TEXT_SOURCE_LANGUAGE_NAMES,
)

DESCRIPTION = "# SeamlessM4T"

TASK_NAMES = [
    "S2ST (Speech to Speech translation)",
    "S2TT (Speech to Text translation)",
    "T2ST (Text to Speech translation)",
    "T2TT (Text to Text translation)",
    "ASR (Automatic Speech Recognition)",
]

AUDIO_SAMPLE_RATE = 16000.0
MAX_INPUT_AUDIO_LENGTH = 60  # in seconds

DEFAULT_TARGET_LANGUAGE = "French"

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
translator = Translator(
    model_name_or_card="multitask_unity_large",
    vocoder_name_or_card="vocoder_36langs",
    device=device,
    sample_rate=AUDIO_SAMPLE_RATE,
)


def predict(
    task_name: str,
    audio_source: str,
    input_audio_mic: str,
    input_audio_file: str,
    input_text: str,
    source_language: str,
    target_language: str,
) -> tuple[tuple[int, np.ndarray] | None, str]:
    task_name = task_name.split()[0]
    source_language_code = LANGUAGE_NAME_TO_CODE[source_language]
    target_language_code = LANGUAGE_NAME_TO_CODE[target_language]

    if task_name in ["S2ST", "S2TT", "ASR"]:
        if audio_source == "microphone":
            input_data = input_audio_mic
        else:
            input_data = input_audio_file

        arr, org_sr = torchaudio.load(input_data)
        new_arr = torchaudio.functional.resample(arr, orig_freq=org_sr, new_freq=AUDIO_SAMPLE_RATE)
        max_length = int(MAX_INPUT_AUDIO_LENGTH * AUDIO_SAMPLE_RATE)
        if new_arr.shape[1] > max_length:
            new_arr = new_arr[:, :max_length]
            gr.Warning(f"Input audio is too long. Only the first {MAX_INPUT_AUDIO_LENGTH} seconds is used.")
        torchaudio.save(input_data, new_arr, sample_rate=int(AUDIO_SAMPLE_RATE))
    else:
        input_data = input_text
    text_out, wav, sr = translator.predict(
        input=input_data,
        task_str=task_name,
        tgt_lang=target_language_code,
        src_lang=source_language_code,
    )
    if task_name in ["S2ST", "T2ST"]:
        return (sr, wav.cpu().detach().numpy()), text_out
    else:
        return None, text_out


def update_audio_ui(audio_source: str) -> tuple[dict, dict]:
    mic = audio_source == "microphone"
    return (
        gr.update(visible=mic, value=None),  # input_audio_mic
        gr.update(visible=not mic, value=None),  # input_audio_file
    )


def update_input_ui(task_name: str) -> tuple[dict, dict, dict, dict]:
    task_name = task_name.split()[0]
    if task_name == "S2ST":
        return (
            gr.update(visible=True),  # audio_box
            gr.update(visible=False),  # input_text
            gr.update(visible=False),  # source_language
            gr.update(
                visible=True, choices=S2ST_TARGET_LANGUAGE_NAMES, value=DEFAULT_TARGET_LANGUAGE
            ),  # target_language
        )
    elif task_name == "S2TT":
        return (
            gr.update(visible=True),  # audio_box
            gr.update(visible=False),  # input_text
            gr.update(visible=False),  # source_language
            gr.update(
                visible=True, choices=S2TT_TARGET_LANGUAGE_NAMES, value=DEFAULT_TARGET_LANGUAGE
            ),  # target_language
        )
    elif task_name == "T2ST":
        return (
            gr.update(visible=False),  # audio_box
            gr.update(visible=True),  # input_text
            gr.update(visible=True),  # source_language
            gr.update(
                visible=True, choices=S2ST_TARGET_LANGUAGE_NAMES, value=DEFAULT_TARGET_LANGUAGE
            ),  # target_language
        )
    elif task_name == "T2TT":
        return (
            gr.update(visible=False),  # audio_box
            gr.update(visible=True),  # input_text
            gr.update(visible=True),  # source_language
            gr.update(
                visible=True, choices=T2TT_TARGET_LANGUAGE_NAMES, value=DEFAULT_TARGET_LANGUAGE
            ),  # target_language
        )
    elif task_name == "ASR":
        return (
            gr.update(visible=True),  # audio_box
            gr.update(visible=False),  # input_text
            gr.update(visible=False),  # source_language
            gr.update(
                visible=True, choices=S2TT_TARGET_LANGUAGE_NAMES, value=DEFAULT_TARGET_LANGUAGE
            ),  # target_language
        )
    else:
        raise ValueError(f"Unknown task: {task_name}")


def update_output_ui(task_name: str) -> tuple[dict, dict]:
    task_name = task_name.split()[0]
    if task_name in ["S2ST", "T2ST"]:
        return (
            gr.update(visible=True, value=None),  # output_audio
            gr.update(value=None),  # output_text
        )
    elif task_name in ["S2TT", "T2TT", "ASR"]:
        return (
            gr.update(visible=False, value=None),  # output_audio
            gr.update(value=None),  # output_text
        )
    else:
        raise ValueError(f"Unknown task: {task_name}")


with gr.Blocks(css="style.css") as demo:
    gr.Markdown(DESCRIPTION)
    gr.DuplicateButton(
        value="Duplicate Space for private use",
        elem_id="duplicate-button",
        visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
    )
    with gr.Group():
        task_name = gr.Dropdown(
            label="Task",
            choices=TASK_NAMES,
            value=TASK_NAMES[0],
        )
        with gr.Row():
            source_language = gr.Dropdown(
                label="Source language",
                choices=TEXT_SOURCE_LANGUAGE_NAMES,
                value="English",
                visible=False,
            )
            target_language = gr.Dropdown(
                label="Target language",
                choices=S2ST_TARGET_LANGUAGE_NAMES,
                value=DEFAULT_TARGET_LANGUAGE,
            )
        with gr.Row() as audio_box:
            audio_source = gr.Radio(
                label="Audio source",
                choices=["file", "microphone"],
                value="file",
            )
            input_audio_mic = gr.Audio(
                label="Input speech",
                type="filepath",
                source="microphone",
                visible=False,
            )
            input_audio_file = gr.Audio(
                label="Input speech",
                type="filepath",
                source="upload",
                visible=True,
            )
        input_text = gr.Textbox(label="Input text", visible=False)
        btn = gr.Button("Translate")
        with gr.Column():
            output_audio = gr.Audio(
                label="Translated speech",
                autoplay=False,
                streaming=False,
                type="numpy",
            )
            output_text = gr.Textbox(label="Translated text")

    audio_source.change(
        fn=update_audio_ui,
        inputs=audio_source,
        outputs=[
            input_audio_mic,
            input_audio_file,
        ],
        queue=False,
        api_name=False,
    )
    task_name.change(
        fn=update_input_ui,
        inputs=task_name,
        outputs=[
            audio_box,
            input_text,
            source_language,
            target_language,
        ],
        queue=False,
        api_name=False,
    ).then(
        fn=update_output_ui,
        inputs=task_name,
        outputs=[output_audio, output_text],
        queue=False,
        api_name=False,
    )

    btn.click(
        fn=predict,
        inputs=[
            task_name,
            audio_source,
            input_audio_mic,
            input_audio_file,
            input_text,
            source_language,
            target_language,
        ],
        outputs=[output_audio, output_text],
        api_name="run",
    )
demo.queue(max_size=50).launch()