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Duplicate from dmatekenya/Chichewa-Automatic-Transcription

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Co-authored-by: Dunstan Matekenya <dmatekenya@users.noreply.huggingface.co>

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  1. .gitattributes +35 -0
  2. README.md +14 -0
  3. app.py +60 -0
  4. requirements.txt +3 -0
.gitattributes ADDED
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README.md ADDED
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+ ---
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+ title: Chichewa Automatic Transcription
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+ emoji: ⚡
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+ colorFrom: pink
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+ colorTo: pink
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+ sdk: gradio
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+ sdk_version: 3.35.2
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+ app_file: app.py
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+ pinned: false
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+ license: openrail
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+ duplicated_from: dmatekenya/Chichewa-Automatic-Transcription
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+ ---
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+
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
app.py ADDED
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+ from transformers import pipeline
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+ from transformers import WhisperForConditionalGeneration, WhisperProcessor, WhisperFeatureExtractor
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+ import gradio as gr
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+ import librosa
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+
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+ # Prepare model for prediction
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+ MODEL_SPECS_ID = "dmatekenya/whisper-small_finetuned_sh_chich"
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+ MODEL_SPECS_BASE_ID = "openai/whisper-small"
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+ MODEL_SPECS_BASE_LAN_SW = "swahili"
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+ MODEL_SPECS_BASE_LAN_SH = "shona"
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+ FEATURE_EXTRACTOR = WhisperFeatureExtractor.from_pretrained(MODEL_SPECS_ID)
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+ PROCESSOR_SH = WhisperProcessor.from_pretrained(MODEL_SPECS_BASE_ID,
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+ language=MODEL_SPECS_BASE_LAN_SH, task="transcribe")
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+ MODEL = WhisperForConditionalGeneration.from_pretrained(MODEL_SPECS_ID)
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+
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+
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+ def transcribe(audio_file):
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+ y, sr = librosa.load(audio_file, sr=16000)
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+
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+ input_features = PROCESSOR_SH(y, return_tensors="pt", sampling_rate=sr).input_features
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+ generated_ids = MODEL.generate(inputs=input_features)
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+
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+ transcription = PROCESSOR_SH.batch_decode(generated_ids, skip_special_tokens=True)[0]
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+
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+ return transcription
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+
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+
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+ def transcribe_audio(mic=None, file=None):
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+ if mic is not None:
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+ audio = mic
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+ elif file is not None:
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+ audio = file
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+ else:
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+ return "You must either provide a mic recording or a file"
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+ transcription = transcribe(audio_file=audio)
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+ return transcription
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+
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+ title = "Transcribe Chichewa Audio"
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+ description = """
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+ <img src="https://i.ibb.co/5nQdGSs/logo.png">
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+ IN THIS DEMO, TEST THE FIRST AUTOMATED SPEECH RECOGNITION (ASR) MODEL FOR CHICHEWA BY TRANSCRIBING YOUR CHICHEWA VOICE NOTES.
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+ FOR AUDIO FILES, PLEASE UPLOAD SHORT VOICE NOTES ONLY (NO LONGER THAN 30 SEC).
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+ """
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+
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+ article = "Read more about the [ChichewaSpeech2Text](https://dmatekenya.github.io/Chichewa-Speech2Text/README.html) project \
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+ and make sure to sign-up for our first [voice note donation event](https://forms.gle/fHLESutofVvb2YFM9) on July 22. \
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+ You stand a chance to win Airtel or TNM units if you choose to participate in the raffle after the event"
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+
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+ gr.Interface(
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+ fn=transcribe_audio,
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+ theme='grass',
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+ title=title,
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+ description=description,
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+ article=article,
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+ inputs=[
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+ gr.Audio(source="microphone", type="filepath", optional=True),
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+ gr.Audio(source="upload", type="filepath", optional=True),
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+ ],
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+ outputs="text",
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+ ).launch()
requirements.txt ADDED
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+ transformers
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+ librosa
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+ torch