Add support for gradio blocks for better GUI

README.md

@@ -1,8 +1,8 @@
 ---
 title: Nemo Multilingual Language Id
-emoji: 🏢
+emoji: 🐠
 colorFrom: blue
-colorTo: blue
+colorTo: gray
 sdk: gradio
 sdk_version: 3.7
 app_file: app.py

app.py

@@ -0,0 +1,138 @@
+import gradio as gr
+import torch
+
+import nemo.collections.asr as nemo_asr
+
+SAMPLE_RATE = 16000
+TITLE = "NeMo ASR Inference on Hugging Face"
+DESCRIPTION = "Demo of all languages supported by NeMo ASR"
+DEFAULT_EN_MODEL = "nvidia/stt_en_conformer_transducer_xlarge"
+
+MARKDOWN = f"""
+# {TITLE}
+
+## {DESCRIPTION}
+"""
+
+CSS = """
+p.big {
+  font-size: 20px;
+}
+"""
+
+ARTICLE = """
+<br><br>
+<p class='big' style='text-align: center'>
+    <a href='https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/asr/intro.html' target='_blank'>NeMo ASR</a> 
+    | 
+    <a href='https://github.com/NVIDIA/NeMo#nvidia-nemo' target='_blank'>Github Repo</a>
+</p>
+"""
+
+SUPPORTED_LANGUAGES = set([])
+SUPPORTED_MODEL_NAMES = set([])
+
+# HF models
+hf_filter = nemo_asr.models.ASRModel.get_hf_model_filter()
+hf_filter.task = "automatic-speech-recognition"
+
+hf_infos = nemo_asr.models.ASRModel.search_huggingface_models(model_filter=hf_filter)
+for info in hf_infos:
+    lang_id = info.modelId.split("_")[1]  # obtains lang id as str
+    SUPPORTED_LANGUAGES.add(lang_id)
+    SUPPORTED_MODEL_NAMES.add(info.modelId)
+
+SUPPORTED_MODEL_NAMES = sorted(list(SUPPORTED_MODEL_NAMES))
+
+model_dict = {model_name: gr.Interface.load(f'models/{model_name}') for model_name in SUPPORTED_MODEL_NAMES}
+
+SUPPORTED_LANG_MODEL_DICT = {}
+for lang in SUPPORTED_LANGUAGES:
+    for model_id in SUPPORTED_MODEL_NAMES:
+        if lang in model_id:
+            # create new lang in dict
+            if lang not in SUPPORTED_LANG_MODEL_DICT:
+                SUPPORTED_LANG_MODEL_DICT[lang] = [model_id]
+            else:
+                SUPPORTED_LANG_MODEL_DICT[lang].append(model_id)
+
+# Sort model names
+for lang in SUPPORTED_LANG_MODEL_DICT.keys():
+    model_ids = SUPPORTED_LANG_MODEL_DICT[lang]
+    model_ids = sorted(model_ids)
+    SUPPORTED_LANG_MODEL_DICT[lang] = model_ids
+
+
+def transcribe(microphone, audio_file, model_name):
+    model = model_dict[model_name]
+
+    warn_output = ""
+    if (microphone is not None) and (audio_file is not None):
+        warn_output = (
+            "WARNING: You've uploaded an audio file and used the microphone. "
+            "The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
+        )
+        audio_data = microphone
+
+    elif (microphone is None) and (audio_file is None):
+        return "ERROR: You have to either use the microphone or upload an audio file"
+
+    elif microphone is not None:
+        audio_data = microphone
+    else:
+        audio_data = audio_file
+
+    try:
+        # Use HF API for transcription
+        transcriptions = model(audio_data)
+
+    except Exception as e:
+        transcriptions = ""
+        warn_output = warn_output + "\n\n"
+        warn_output += (
+            f"The model `{model_name}` is currently loading and cannot be used "
+            f"for transcription.\n"
+            f"Please try another model or wait a few minutes."
+        )
+
+    return warn_output + transcriptions
+
+
+demo = gr.Blocks(title=TITLE, css=CSS)
+
+with demo:
+    header = gr.Markdown(MARKDOWN)
+
+    with gr.Row() as row:
+        file_upload = gr.components.Audio(source="upload", type='filepath', label='Upload File')
+        microphone = gr.components.Audio(source="microphone", type='filepath', label='Microphone')
+
+    lang_selector = gr.components.Dropdown(
+        choices=sorted(list(SUPPORTED_LANGUAGES)), value="en", type="value", label="Languages", interactive=True,
+    )
+    models_in_lang = gr.components.Dropdown(
+        choices=sorted(list(SUPPORTED_LANG_MODEL_DICT["en"])),
+        value=DEFAULT_EN_MODEL,
+        label="Models",
+        interactive=True,
+    )
+
+    def update_models_with_lang(lang):
+        models_names = sorted(list(SUPPORTED_LANG_MODEL_DICT[lang]))
+        default = models_names[0]
+
+        if lang == 'en':
+            default = DEFAULT_EN_MODEL
+        return models_in_lang.update(choices=models_names, value=default)
+
+    lang_selector.change(update_models_with_lang, inputs=[lang_selector], outputs=[models_in_lang])
+
+    transcript = gr.components.Label(label='Transcript')
+
+    run = gr.components.Button('Transcribe')
+    run.click(transcribe, inputs=[microphone, file_upload, models_in_lang], outputs=[transcript])
+
+    gr.components.HTML(ARTICLE)
+
+demo.queue(concurrency_count=1)
+demo.launch()

packages.txt

@@ -0,0 +1,2 @@
+ffmpeg
+libsndfile1

requirements.txt

@@ -0,0 +1 @@
+nemo_toolkit[asr]