Spaces:
Runtime error
Runtime error
Added file conversion to uploaded files. Added chunking to allow transcribing long audio files.
341e55d
| import streamlit as st | |
| from transformers import pipeline | |
| from torch import cuda | |
| import torchaudio | |
| import torchaudio.functional as F | |
| from pydub import AudioSegment | |
| import logging | |
| import io | |
| class ASR: | |
| def __init__(self): | |
| self.model_name = "viktor-enzell/wav2vec2-large-voxrex-swedish-4gram" | |
| self.device = cuda.current_device() if cuda.is_available() else -1 | |
| self.model = None | |
| def load_model(self): | |
| self.model = pipeline(model=self.model_name, device=self.device) | |
| def run_inference(self, file): | |
| audio = self.load_16khz_audio(file) | |
| return self.model(audio, chunk_length_s=10)["text"].lower() | |
| def load_16khz_audio(file): | |
| waveform, sample_rate = torchaudio.load(file) | |
| if sample_rate == 16_000: | |
| waveform = waveform[0] | |
| else: | |
| waveform = F.resample(waveform, sample_rate, 16_000)[0] | |
| return waveform.numpy() | |
| def load_model(): | |
| asr = ASR() | |
| asr.load_model() | |
| return asr | |
| def run_inference(asr, file): | |
| return asr.run_inference(file) | |
| def convert_uploaded_file_to_wav(file): | |
| try: | |
| media_type = file.type.split("/")[0] | |
| file_extension = file.name.split(".")[-1] | |
| if media_type != "audio" and media_type != "video": | |
| return None | |
| if file_extension == "wav": | |
| return file | |
| audio = AudioSegment.from_file(file, file_extension) | |
| in_memory_buffer = io.BytesIO() | |
| return audio.export(in_memory_buffer, format="wav") | |
| except Exception as e: | |
| logging.exception(e) | |
| return None | |
| if __name__ == "__main__": | |
| st.set_page_config( | |
| page_title="Swedish Speech-to-Text", | |
| page_icon="🎙️" | |
| ) | |
| st.image( | |
| "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/320/apple/325/studio-microphone_1f399-fe0f.png", | |
| width=100, | |
| ) | |
| st.markdown(""" | |
| # Swedish Speech-to-text | |
| Generate and download high-quality Swedish transcripts for your audio and video files. The speech-to-text model is KBLab's wav2vec 2.0 large VoxRex Swedish (C) with a 4-gram language model, which you can access [here](https://huggingface.co/viktor-enzell/wav2vec2-large-voxrex-swedish-4gram). | |
| """) | |
| with st.spinner(text="Loading model..."): | |
| asr = load_model() | |
| uploaded_file = st.file_uploader("Choose a file") | |
| if uploaded_file is not None: | |
| file = convert_uploaded_file_to_wav(uploaded_file) | |
| if file is None: | |
| st.error( | |
| "There was a problem handling the uploaded file. Try again using an audio or video file.") | |
| else: | |
| with st.spinner(text="Transcribing..."): | |
| transcript = run_inference(asr, file) | |
| st.download_button("Download transcript", | |
| transcript, "transcript.txt") | |
| with st.expander("Transcript", expanded=True): | |
| st.write(transcript) | |