Create app.py

app.py

@@ -0,0 +1,67 @@
+import gradio as gr
+import torchaudio
+import torch
+from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC
+from transformers import Speech2Text2Processor, Speech2Text2ForConditionalGeneration
+from transformers import Wav2Vec2Processor, Wav2Vec2ForSequenceClassification
+
+# Load the models
+asr_model = Wav2Vec2ForCTC.from_pretrained("facebook/mms-1b-all")
+asr_processor = Wav2Vec2Processor.from_pretrained("facebook/mms-1b-all")
+
+tts_model = Speech2Text2ForConditionalGeneration.from_pretrained("facebook/mms-tts")
+tts_processor = Speech2Text2Processor.from_pretrained("facebook/mms-tts")
+
+lid_model = Wav2Vec2ForSequenceClassification.from_pretrained("facebook/mms-lid-1024")
+lid_processor = Wav2Vec2Processor.from_pretrained("facebook/mms-lid-1024")
+
+# ASR Function
+def asr_transcribe(audio):
+    inputs = asr_processor(audio, sampling_rate=16000, return_tensors="pt", padding=True)
+    with torch.no_grad():
+        logits = asr_model(**inputs).logits
+    predicted_ids = torch.argmax(logits, dim=-1)
+    transcription = asr_processor.batch_decode(predicted_ids)
+    return transcription[0]
+
+# TTS Function
+def tts_synthesize(text):
+    inputs = tts_processor(text, return_tensors="pt", padding=True)
+    with torch.no_grad():
+        generated_ids = tts_model.generate(**inputs)
+    audio = tts_processor.batch_decode(generated_ids, skip_special_tokens=True)
+    return audio[0]
+
+# Language ID Function
+def identify_language(audio):
+    inputs = lid_processor(audio, sampling_rate=16000, return_tensors="pt", padding=True)
+    with torch.no_grad():
+        logits = lid_model(**inputs).logits
+    predicted_ids = torch.argmax(logits, dim=-1)
+    language = lid_processor.batch_decode(predicted_ids)
+    return language[0]
+
+# Define the Gradio interfaces
+with gr.Blocks() as demo:
+    with gr.Tab("ASR"):
+        gr.Markdown("## Automatic Speech Recognition (ASR)")
+        audio_input = gr.Audio(source="microphone", type="numpy")
+        text_output = gr.Textbox(label="Transcription")
+        gr.Button("Clear", clear_audio_input)
+        gr.Button("Submit", fn=asr_transcribe, inputs=audio_input, outputs=text_output)
+        
+    with gr.Tab("TTS"):
+        gr.Markdown("## Text-to-Speech (TTS)")
+        text_input = gr.Textbox(label="Text")
+        audio_output = gr.Audio(label="Audio Output")
+        gr.Button("Clear", clear_text_input)
+        gr.Button("Submit", fn=tts_synthesize, inputs=text_input, outputs=audio_output)
+
+    with gr.Tab("Language ID"):
+        gr.Markdown("## Language Identification (LangID)")
+        audio_input = gr.Audio(source="microphone", type="numpy")
+        language_output = gr.Textbox(label="Identified Language")
+        gr.Button("Clear", clear_audio_input)
+        gr.Button("Submit", fn=identify_language, inputs=audio_input, outputs=language_output)
+
+demo.launch()