Update app.py

app.py

@@ -1,274 +1,230 @@
-#!/usr/bin/env python3
-#
-# Copyright      2022-2023  Xiaomi Corp.        (authors: Fangjun Kuang)
-#
-# See LICENSE for clarification regarding multiple authors
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-# References:
-# https://gradio.app/docs/#dropdown
-
-import os
-import time
-import uuid
-from datetime import datetime
-
-import gradio as gr
-import soundfile as sf
-
-from model import get_pretrained_model, language_to_models
-
-
-def MyPrint(s):
-    now = datetime.now()
-    date_time = now.strftime("%Y-%m-%d %H:%M:%S.%f")
-    print(f"{date_time}: {s}")
-
-
-title = "# Next-gen Kaldi: Text-to-speech (TTS)"
-
-description = """
-This space shows how to convert text to speech with Next-gen Kaldi.
-
-It is running on CPU within a docker container provided by Hugging Face.
-
-See more information by visiting the following links:
-
-- <https://github.com/k2-fsa/sherpa-onnx>
-
-If you want to deploy it locally, please see
-<https://k2-fsa.github.io/sherpa/>
-
-If you want to use Android APKs, please see
-<https://k2-fsa.github.io/sherpa/onnx/tts/apk.html>
-
-If you want to use Android text-to-speech engine APKs, please see
-<https://k2-fsa.github.io/sherpa/onnx/tts/apk-engine.html>
-
-If you want to download an all-in-one exe for Windows, please see
-<https://github.com/k2-fsa/sherpa-onnx/releases/tag/tts-models>
-
-"""
-
-# css style is copied from
-# https://huggingface.co/spaces/alphacep/asr/blob/main/app.py#L113
-css = """
-.result {display:flex;flex-direction:column}
-.result_item {padding:15px;margin-bottom:8px;border-radius:15px;width:100%}
-.result_item_success {background-color:mediumaquamarine;color:white;align-self:start}
-.result_item_error {background-color:#ff7070;color:white;align-self:start}
-"""
-
-examples = [
-    [
-        "Chinese (Mandarin, 普通话)",
-        "csukuangfj/matcha-icefall-zh-baker|1 speaker",
-        "某某银行的副行长和一些行政领导表示，他们去过长江和长白山; 经济不断增长。2024年12月31号，拨打110或者18920240511。123456块钱。",
-        0,
-        1.0,
-    ],
-    [
-        "Chinese (Mandarin, 普通话)",
-        "csukuangfj/vits-zh-hf-fanchen-wnj|1 speaker",
-        "在一个阳光明媚的夏天，小马、小羊和小狗它们一块儿在广阔的草地上，嬉戏玩耍，这时小猴来了，还带着它心爱的足球活蹦乱跳地跑前、跑后教小马、小羊、小狗踢足球。",
-        0,
-        1.0,
-    ],
-    [
-        "Chinese (Mandarin, 普通话)",
-        "csukuangfj/vits-zh-hf-fanchen-C|187 speakers",
-        '小米的使命是，始终坚持做"感动人心、价格厚道"的好产品，让全球每个人都能享受科技带来的美好生活。',
-        0,
-        1.0,
-    ],
-    ["Min-nan (闽南话)", "csukuangfj/vits-mms-nan", "ài piaǸ chiah ē iaN̂", 0, 1.0],
-    ["Thai", "csukuangfj/vits-mms-tha", "ฉันรักคุณ", 0, 1.0],
-    [
-        "Chinese (Mandarin, 普通话)",
-        "csukuangfj/sherpa-onnx-vits-zh-ll|5 speakers",
-        "当夜幕降临，星光点点，伴随着微风拂面，我在静谧中感受着时光的流转，思念如涟漪荡漾，梦境如画卷展开，我与自然融为一体，沉静在这片宁静的美丽之中，感受着生命的奇迹与温柔。",
-        2,
-        1.0,
-    ],
-]
-
-
-def update_model_dropdown(language: str):
-    if language in language_to_models:
-        choices = language_to_models[language]
-        return gr.Dropdown(
-            choices=choices,
-            value=choices[0],
-            interactive=True,
-        )
-
-    raise ValueError(f"Unsupported language: {language}")
-
-
-def build_html_output(s: str, style: str = "result_item_success"):
-    return f"""
-    <div class='result'>
-        <div class='result_item {style}'>
-          {s}
-        </div>
-    </div>
-    """
-
-
-def process(language: str, repo_id: str, text: str, sid: str, speed: float):
-    MyPrint(f"Input text: {text}. sid: {sid}, speed: {speed}")
-    sid = int(sid)
-    tts = get_pretrained_model(repo_id, speed)
-
-    start = time.time()
-    audio = tts.generate(text, sid=sid)
-    end = time.time()
-
-    if len(audio.samples) == 0:
-        raise ValueError(
-            "Error in generating audios. Please read previous error messages."
-        )
-
-    duration = len(audio.samples) / audio.sample_rate
-
-    elapsed_seconds = end - start
-    rtf = elapsed_seconds / duration
-
-    info = f"""
-    Wave duration  : {duration:.3f} s <br/>
-    Processing time: {elapsed_seconds:.3f} s <br/>
-    RTF: {elapsed_seconds:.3f}/{duration:.3f} = {rtf:.3f} <br/>
-    """
-
-    MyPrint(info)
-    MyPrint(f"\nrepo_id: {repo_id}\ntext: {text}\nsid: {sid}\nspeed: {speed}")
-
-    filename = str(uuid.uuid4())
-    filename = f"{filename}.wav"
-    sf.write(
-        filename,
-        audio.samples,
-        samplerate=audio.sample_rate,
-        subtype="PCM_16",
-    )
-
-    return filename, build_html_output(info)
-
-
-demo = gr.Blocks(css=css)
-
-
-with demo:
-    gr.Markdown(title)
-    language_choices = list(language_to_models.keys())
-
-    language_radio = gr.Radio(
-        label="Language",
-        choices=language_choices,
-        value=language_choices[0],
-    )
-
-    model_dropdown = gr.Dropdown(
-        choices=language_to_models[language_choices[0]],
-        label="Select a model",
-        value=language_to_models[language_choices[0]][0],
-    )
-
-    language_radio.change(
-        update_model_dropdown,
-        inputs=language_radio,
-        outputs=model_dropdown,
-    )
-
-    with gr.Tabs():
-        with gr.TabItem("Please input your text"):
-            input_text = gr.Textbox(
-                label="Input text",
-                info="Your text",
-                lines=3,
-                placeholder="Please input your text here",
-            )
-
-            input_sid = gr.Textbox(
-                label="Speaker ID",
-                info="Speaker ID",
-                lines=1,
-                max_lines=1,
-                value="0",
-                placeholder="Speaker ID. Valid only for mult-speaker model",
-            )
-
-            input_speed = gr.Slider(
-                minimum=0.1,
-                maximum=10,
-                value=1,
-                step=0.1,
-                label="Speed (larger->faster; smaller->slower)",
-            )
-
-            input_button = gr.Button("Submit")
-
-            output_audio = gr.Audio(label="Output")
-
-            output_info = gr.HTML(label="Info")
-
-            gr.Examples(
-                examples=examples,
-                fn=process,
-                inputs=[
-                    language_radio,
-                    model_dropdown,
-                    input_text,
-                    input_sid,
-                    input_speed,
-                ],
-                outputs=[
-                    output_audio,
-                    output_info,
-                ],
-            )
-
-        input_button.click(
-            process,
-            inputs=[
-                language_radio,
-                model_dropdown,
-                input_text,
-                input_sid,
-                input_speed,
-            ],
-            outputs=[
-                output_audio,
-                output_info,
-            ],
-        )
-
-    gr.Markdown(description)
-
-
-def download_espeak_ng_data():
-    os.system(
-        """
-    cd /tmp
-    wget -qq https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/espeak-ng-data.tar.bz2
-    tar xf espeak-ng-data.tar.bz2
-    """
-    )
-
-
-if __name__ == "__main__":
-    download_espeak_ng_data()
-    formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
-
-    demo.launch()
+#!/usr/bin/env python3
+
+import os
+import time
+import uuid
+from datetime import datetime
+
+import gradio as gr
+import soundfile as sf
+
+from model import get_pretrained_model, language_to_models
+
+
+def MyPrint(s):
+    now = datetime.now()
+    date_time = now.strftime("%Y-%m-%d %H:%M:%S.%f")
+    print(f"{date_time}: {s}")
+
+
+title = "# Next-gen Kaldi: Text-to-speech (TTS)"
+
+description = """
+This space shows how to convert text to speech with Next-gen Kaldi (Sherpa-ONNX).
+
+Running on CPU in a Docker container from Hugging Face.
+
+Useful links:
+
+- <https://github.com/k2-fsa/sherpa-onnx>
+- <https://k2-fsa.github.io/sherpa/>
+- <https://github.com/k2-fsa/sherpa-onnx/releases/tag/tts-models>
+"""
+
+css = """
+.result {display:flex;flex-direction:column}
+.result_item {padding:15px;margin-bottom:8px;border-radius:15px;width:100%}
+.result_item_success {background-color:mediumaquamarine;color:white;align-self:start}
+.result_item_error {background-color:#ff7070;color:white;align-self:start}
+"""
+
+examples = [
+    [
+        "English",
+        "csukuangfj/vits-piper-en_US-libritts-rhea|1 speaker",
+        "Hello! This is a test of the text-to-speech demo powered by Sherpa-ONNX.",
+        0,
+        1.0,
+    ],
+    [
+        "English",
+        "csukuangfj/vits-piper-en_GB-alba|1 speaker",
+        "Welcome to the world of AI voice generation. Enjoy the experience.",
+        0,
+        1.0,
+    ],
+    [
+        "English",
+        "csukuangfj/vits-piper-en_US-lessac-medium|1 speaker",
+        "Real-time voice synthesis helps developers build smarter applications.",
+        0,
+        1.0,
+    ],
+]
+
+
+def update_model_dropdown(language: str):
+    if language in language_to_models:
+        choices = language_to_models[language]
+        return gr.Dropdown(
+            choices=choices,
+            value=choices[0],
+            interactive=True,
+        )
+
+    raise ValueError(f"Unsupported language: {language}")
+
+
+def build_html_output(s: str, style: str = "result_item_success"):
+    return f"""
+    <div class='result'>
+        <div class='result_item {style}'>
+          {s}
+        </div>
+    </div>
+    """
+
+
+def process(language: str, repo_id: str, text: str, sid: str, speed: float):
+    MyPrint(f"Input text: {text}. sid: {sid}, speed: {speed}")
+    sid = int(sid)
+    tts = get_pretrained_model(repo_id, speed)
+
+    start = time.time()
+    audio = tts.generate(text, sid=sid)
+    end = time.time()
+
+    if len(audio.samples) == 0:
+        raise ValueError(
+            "Error in generating audios. Please read previous error messages."
+        )
+
+    duration = len(audio.samples) / audio.sample_rate
+
+    elapsed_seconds = end - start
+    rtf = elapsed_seconds / duration
+
+    info = f"""
+    Wave duration  : {duration:.3f} s <br/>
+    Processing time: {elapsed_seconds:.3f} s <br/>
+    RTF: {elapsed_seconds:.3f}/{duration:.3f} = {rtf:.3f} <br/>
+    """
+
+    MyPrint(info)
+    MyPrint(f"\nrepo_id: {repo_id}\ntext: {text}\nsid: {sid}\nspeed: {speed}")
+
+    filename = str(uuid.uuid4())
+    filename = f"{filename}.wav"
+    sf.write(
+        filename,
+        audio.samples,
+        samplerate=audio.sample_rate,
+        subtype="PCM_16",
+    )
+
+    return filename, build_html_output(info)
+
+
+demo = gr.Blocks(css=css)
+
+with demo:
+    gr.Markdown(title)
+    language_choices = list(language_to_models.keys())
+
+    language_radio = gr.Radio(
+        label="Language",
+        choices=language_choices,
+        value="English",  # Default language
+    )
+
+    model_dropdown = gr.Dropdown(
+        choices=language_to_models["English"],  # Default model list
+        label="Select a model",
+        value=language_to_models["English"][0],  # Default model
+    )
+
+    language_radio.change(
+        update_model_dropdown,
+        inputs=language_radio,
+        outputs=model_dropdown,
+    )
+
+    with gr.Tabs():
+        with gr.TabItem("Please input your text"):
+            input_text = gr.Textbox(
+                label="Input text",
+                info="Your text",
+                lines=3,
+                placeholder="Please input your text here",
+            )
+
+            input_sid = gr.Textbox(
+                label="Speaker ID",
+                info="Speaker ID",
+                lines=1,
+                max_lines=1,
+                value="0",
+                placeholder="Speaker ID. Valid only for multi-speaker model",
+            )
+
+            input_speed = gr.Slider(
+                minimum=0.1,
+                maximum=10,
+                value=1,
+                step=0.1,
+                label="Speed (larger->faster; smaller->slower)",
+            )
+
+            input_button = gr.Button("Submit")
+
+            output_audio = gr.Audio(label="Output")
+
+            output_info = gr.HTML(label="Info")
+
+            gr.Examples(
+                examples=examples,
+                fn=process,
+                inputs=[
+                    language_radio,
+                    model_dropdown,
+                    input_text,
+                    input_sid,
+                    input_speed,
+                ],
+                outputs=[
+                    output_audio,
+                    output_info,
+                ],
+            )
+
+        input_button.click(
+            process,
+            inputs=[
+                language_radio,
+                model_dropdown,
+                input_text,
+                input_sid,
+                input_speed,
+            ],
+            outputs=[
+                output_audio,
+                output_info,
+            ],
+        )
+
+    gr.Markdown(description)
+
+
+def download_espeak_ng_data():
+    os.system(
+        """
+    cd /tmp
+    wget -qq https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/espeak-ng-data.tar.bz2
+    tar xf espeak-ng-data.tar.bz2
+    """
+    )
+
+
+if __name__ == "__main__":
+    download_espeak_ng_data()
+    demo.launch()