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| import gradio as gr | |
| import speech_recognition as sr | |
| from time import time | |
| import threading | |
| from pydub import AudioSegment | |
| from pydub.playback import play | |
| import io | |
| # Global variables | |
| is_recording = False | |
| start_beep = AudioSegment.silent(duration=200).append(AudioSegment.from_wav(io.BytesIO(b''), crossfade=100) | |
| end_beep = AudioSegment.silent(duration=200).append(AudioSegment.from_wav(io.BytesIO(b'')), crossfade=100) | |
| def play_start_sound(): | |
| try: | |
| play(start_beep) | |
| except: | |
| pass | |
| def play_end_sound(): | |
| try: | |
| play(end_beep) | |
| except: | |
| pass | |
| def start_recording(audio_time_limit): | |
| global is_recording | |
| is_recording = True | |
| recognizer = sr.Recognizer() | |
| microphone = sr.Microphone() | |
| play_start_sound() | |
| with microphone as source: | |
| recognizer.adjust_for_ambient_noise(source, duration=0.5) | |
| try: | |
| audio = recognizer.listen(source, timeout=3, phrase_time_limit=audio_time_limit) | |
| text = recognizer.recognize_google(audio) | |
| return text | |
| except sr.WaitTimeoutError: | |
| return "" | |
| except sr.UnknownValueError: | |
| return "" | |
| except Exception as e: | |
| print(f"Error: {str(e)}") | |
| return "" | |
| finally: | |
| play_end_sound() | |
| is_recording = False | |
| def transcribe_audio(audio_time_limit=10): | |
| def execute_recording(): | |
| nonlocal result | |
| result = start_recording(audio_time_limit) | |
| result = "" | |
| recording_thread = threading.Thread(target=execute_recording) | |
| recording_thread.start() | |
| start_time = time() | |
| while is_recording and (time() - start_time) < audio_time_limit: | |
| time_elapsed = time() - start_time | |
| time_left = max(0, audio_time_limit - time_elapsed) | |
| progress = 1 - (time_left / audio_time_limit) | |
| yield {"__type__": "update", "value": f"🎤 Recording... {time_left:.1f}s left", "visible": True}, {"__type__": "update", "value": "", "visible": True} | |
| gr.sleep(0.1) | |
| recording_thread.join() | |
| yield {"__type__": "update", "value": "✅ Done!", "visible": True}, {"__type__": "update", "value": result, "visible": True} | |
| def create_ui(): | |
| css = """ | |
| .mic-button { | |
| background: linear-gradient(45deg, #FF3366, #BA265D) !important; | |
| border: none !important; | |
| color: white !important; | |
| padding: 12px !important; | |
| border-radius: 50% !important; | |
| height: 50px !important; | |
| width: 50px !important; | |
| margin-left: 10px !important; | |
| } | |
| .mic-button:hover { | |
| transform: scale(1.05) !important; | |
| } | |
| .input-with-mic { | |
| display: flex !important; | |
| align-items: center !important; | |
| gap: 10px !important; | |
| } | |
| .status-message { | |
| font-style: italic; | |
| color: #666; | |
| margin-top: 5px; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| gr.Markdown("## 🎤 Speech to Text Converter") | |
| with gr.Group(): | |
| with gr.Row(): | |
| text_input = gr.Textbox( | |
| label="Your Input", | |
| placeholder="Click the mic button and speak...", | |
| elem_classes=["input-box"], | |
| scale=9 | |
| ) | |
| mic_button = gr.Button( | |
| "🎤", | |
| elem_classes=["mic-button"], | |
| scale=1 | |
| ) | |
| status_display = gr.Textbox( | |
| label="Status", | |
| visible=False, | |
| interactive=False, | |
| elem_classes=["status-message"] | |
| ) | |
| mic_button.click( | |
| fn=transcribe_audio, | |
| inputs=[gr.Slider(5, 30, value=10, label="Recording time limit (seconds)")], | |
| outputs=[status_display, text_input], | |
| show_progress="hidden" | |
| ) | |
| gr.Examples( | |
| examples=["Hello world", "How are you today?", "Please convert my speech to text"], | |
| inputs=text_input, | |
| label="Try these examples:" | |
| ) | |
| return demo | |
| if __name__ == "__main__": | |
| demo = create_ui() | |
| demo.launch(debug=True) |