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| import gradio as gr | |
| import pandas as pd | |
| from css_html_js import custom_css | |
| TITLE = """<h1 align="center" id="space-title">🇲🇾 Malaysian Speech-to-Text Leaderboard</h1>""" | |
| INTRODUCTION_TEXT = """ | |
| 📐 The 🇲🇾 Malaysian Speech-to-Text Leaderboard aims to track, rank and evaluate Malaysian Speech-to-Text models. All notebooks at https://github.com/mesolitica/malaysian-stt-benchmarks | |
| ## Dataset | |
| 📈 We evaluate models based on 3 datasets, | |
| 1. Malaya-Speech test set, Malay language, https://huggingface.co/datasets/mesolitica/speech-test-set/tree/main/malaya-speech | |
| 2. Fleurs MS-MY test set, Malay language, https://huggingface.co/datasets/mesolitica/speech-test-set/tree/main/fleurs-ms-my | |
| 3. IMDA TTS first 700 audio files, English language but with Manglish slang, https://huggingface.co/datasets/mesolitica/IMDA-TTS | |
| ## Heavy postprocess test set | |
| 1. We filtered test set that contain numbers because malaya-speech transducer trained on normalized numbers. | |
| 2. We lower case because malaya-speech transducer trained on lower case. | |
| 3. We removed punctuation because malaya-speech transducer trained without punctuation. | |
| """ | |
| open_source = [ | |
| { | |
| 'model': 'goodtape.io', | |
| 'model size FP16 (MB)': None, | |
| 'Malaya-Speech test CER': 0.09504487340205486, | |
| 'Malaya-Speech test WER': 0.1691902868373457, | |
| 'Fleurs MY-MS CER': 0.03643102801583697, | |
| 'Fleurs MY-MS WER': 0.08672758155453257, | |
| }, | |
| { | |
| 'model': 'openai/whisper-large-v3', | |
| 'model size FP16 (MB)': 3090, | |
| 'Malaya-Speech test CER': 0.0349251317825172, | |
| 'Malaya-Speech test WER': 0.1032828282828283, | |
| 'Fleurs MY-MS CER': 0.026055551396846878, | |
| 'Fleurs MY-MS WER': 0.07652049926522007, | |
| 'IMDA TTS CER': 0.016648493852990828, | |
| 'IMDA TTS WER': 0.0386282289139432, | |
| }, | |
| { | |
| 'model': 'openai/whisper-medium', | |
| 'model size FP16 (MB)': 1530, | |
| 'Malaya-Speech test CER': 0.05064920144820262, | |
| 'Malaya-Speech test WER': 0.17534205321090568, | |
| 'Fleurs MY-MS CER': 0.04366882208520179, | |
| 'Fleurs MY-MS WER': 0.13546055192128273, | |
| 'IMDA TTS CER': 0.02065587879424904, | |
| 'IMDA TTS WER': 0.047277690563404855, | |
| }, | |
| { | |
| 'model': 'openai/whisper-small', | |
| 'model size FP16 (MB)': 483.5, | |
| 'Malaya-Speech test CER': 0.07485209857268262, | |
| 'Malaya-Speech test WER': 0.25748516055893106, | |
| 'Fleurs MY-MS CER': 0.06781078047622793, | |
| 'Fleurs MY-MS WER': 0.21953142859857497, | |
| 'IMDA TTS CER': 0.024812471688517194, | |
| 'IMDA TTS WER': 0.058901277294134434, | |
| }, | |
| { | |
| 'model': 'openai/whisper-base', | |
| 'model size FP16 (MB)': 145, | |
| 'Malaya-Speech test CER': 0.3574879236610538, | |
| 'Malaya-Speech test WER': 0.8303456599563157, | |
| 'Fleurs MY-MS CER': 0.1319124653794061, | |
| 'Fleurs MY-MS WER': 0.40499286081235003, | |
| 'IMDA TTS CER': 0.03914533450681607, | |
| 'IMDA TTS WER': 0.08951682444539587, | |
| }, | |
| { | |
| 'model': 'openai/whisper-tiny', | |
| 'model size FP16 (MB)': 75.5, | |
| 'Malaya-Speech test CER': 0.26941094281472105, | |
| 'Malaya-Speech test WER': 0.7414099751189915, | |
| 'Fleurs MY-MS CER': 0.38749733168917505, | |
| 'Fleurs MY-MS WER': 0.812253445128297, | |
| 'IMDA TTS CER': 0.048805770734828904, | |
| 'IMDA TTS WER': 0.11150629529200957, | |
| }, | |
| { | |
| 'model': 'mesolitica/malaysian-whisper-medium', | |
| 'model size FP16 (MB)': 1530, | |
| 'Malaya-Speech test CER': 0.05622483776367814, | |
| 'Malaya-Speech test WER': 0.14406629724252673, | |
| 'Fleurs MY-MS CER': 0.025543266604368554, | |
| 'Fleurs MY-MS WER': 0.07940219915492629, | |
| 'IMDA TTS CER': 0.01971214262944062, | |
| 'IMDA TTS WER': 0.047223078508792794, | |
| }, | |
| { | |
| 'model': 'mesolitica/malaysian-whisper-small', | |
| 'model size FP16 (MB)': 483.5, | |
| 'Malaya-Speech test CER': 0.049162419174983304, | |
| 'Malaya-Speech test WER': 0.15926901346983313, | |
| 'Fleurs MY-MS CER': 0.035517572531147, | |
| 'Fleurs MY-MS WER': 0.10938718963023729, | |
| 'IMDA TTS CER': 0.024228721439634855, | |
| 'IMDA TTS WER': 0.05546294182008469, | |
| }, | |
| { | |
| 'model': 'mesolitica/malaysian-whisper-base', | |
| 'model size FP16 (MB)': 145, | |
| 'Malaya-Speech test CER': 0.07242006488452603, | |
| 'Malaya-Speech test WER': 0.22081683495617924, | |
| 'Fleurs MY-MS CER': 0.06639564802362424, | |
| 'Fleurs MY-MS WER': 0.19675812232021192, | |
| 'IMDA TTS CER': 0.03982418421412676, | |
| 'IMDA TTS WER': 0.08917690642690643, | |
| }, | |
| { | |
| 'model': 'mesolitica/malaysian-whisper-tiny', | |
| 'model size FP16 (MB)': 75.5, | |
| 'Malaya-Speech test CER': 0.09423990117534763, | |
| 'Malaya-Speech test WER': 0.295029492365558, | |
| 'Fleurs MY-MS CER': 0.13390519685940314, | |
| 'Fleurs MY-MS WER': 0.3461808122686204, | |
| 'IMDA TTS CER': 0.07957313474501154, | |
| 'IMDA TTS WER': 0.1421708648494363, | |
| }, | |
| { | |
| 'model': 'mesolitica/conformer-large-malay-whisper', | |
| 'model size FP16 (MB)': 206.5, | |
| 'Malaya-Speech test CER': 0.025933167255719317, | |
| 'Malaya-Speech test WER': 0.0912131356803488, | |
| 'Fleurs MY-MS CER': 0.02548791948171514, | |
| 'Fleurs MY-MS WER': 0.08376713097429746, | |
| }, | |
| { | |
| 'model': 'mesolitica/conformer-medium-malay-whisper', | |
| 'model size FP16 (MB)': 121.5, | |
| 'Malaya-Speech test CER': 0.024955598713609053, | |
| 'Malaya-Speech test WER': 0.09315638444736804, | |
| 'Fleurs MY-MS CER': 0.029205645523910067, | |
| 'Fleurs MY-MS WER': 0.09253131557833799, | |
| }, | |
| { | |
| 'model': 'mesolitica/conformer-medium-mixed', | |
| 'model size FP16 (MB)': 121.5, | |
| 'Malaya-Speech test CER': 0.034618711056551774, | |
| 'Malaya-Speech test WER': 0.11179440626161938, | |
| 'Fleurs MY-MS CER': 0.032894184549728075, | |
| 'Fleurs MY-MS WER': 0.1026977414887425, | |
| }, | |
| { | |
| 'model': 'mesolitica/conformer-tiny-ctc + mesolitica/kenlm-pseudolabel-whisper-large-v3', | |
| 'model size FP16 (MB)': 7.9, | |
| 'Malaya-Speech test CER': 0.0612581761581601, | |
| 'Malaya-Speech test WER': 0.21302693966628394, | |
| 'Fleurs MY-MS CER': 0.07573301800412188, | |
| 'Fleurs MY-MS WER': 0.2527434609577528, | |
| }, | |
| { | |
| 'model': 'mesolitica/conformer-12M-ctc + mesolitica/kenlm-pseudolabel-whisper-large-v3', | |
| 'model size FP16 (MB)': 24.2, | |
| 'Malaya-Speech test CER': 0.06941749946814912, | |
| 'Malaya-Speech test WER': 0.22261096523391607, | |
| 'Fleurs MY-MS CER': 0.07657934690019219, | |
| 'Fleurs MY-MS WER': 0.263075623142674, | |
| }, | |
| ] | |
| data = pd.DataFrame(open_source) | |
| demo = gr.Blocks(css=custom_css) | |
| with demo: | |
| gr.HTML(TITLE) | |
| gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text") | |
| gr.DataFrame(data) | |
| demo.launch() |