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--- | ||
title: OpenAI Whisper and it's amazing power to do finetuning | ||
author: Kurian Benoy | ||
subtitle: Talk Page for my talk @ Pycon India 2023, Hyderabad | ||
date: 2023-10-01 | ||
date-format: full | ||
categories: [conference, fossasia, Audio, Deep learning, SMC, "Talk Page"] | ||
lang: en | ||
toc: true | ||
comments: false | ||
format: | ||
html: | ||
highlight-style: a11y | ||
theme: | ||
light: flatly | ||
dark: darkly | ||
--- | ||
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## Links to talk | ||
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- [Slides](../../../talks/pyconindia-2023/pyconind.qmd) | ||
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- Scheduled Time: Sunday, October 1, 2023, 11:00 AM IST | ||
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- [Malayalam ASR Benchmarking project](https://github.com/kurianbenoy/malayalam_asr_benchmarking) | ||
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- [Results for Common Voice 11 benchmarking](https://huggingface.co/datasets/kurianbenoy/malayalam_common_voice_benchmarking) | ||
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- [Results for SMC MSC benchmarking](https://huggingface.co/datasets/kurianbenoy/malayalam_msc_benchmarking) | ||
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## Talk in 30 seconds | ||
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I talked about what is OpenAI whisper and some of it's amazing feature. I highlighted the | ||
importance of fine-tuning Whisper in low-resource language like Malayalam which is able to get | ||
almost 90% accuracy compared to -10% accuracy of OpenAI whisper model weights. The results where | ||
calculated with a new github project called [malayalam_asr_benchmarking created by me](https://github.com/kurianbenoy/malayalam_asr_benchmarking). | ||
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