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@@ -95,13 +96,13 @@ <h2> 📊 Available Benchmarks</h2>
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The package helps integrate and evaluate new audio tokenizers in speech tasks of great interest such as <i>speech recognition</i>, <i>speaker identification</i>, <i>emotion recognition</i>, <i>keyword spotting</i>, <i>intent classification</i>, <i>speech enhancement</i>, <i>separation</i>, <i>text-to-speech</i>, and many more.
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<br><br>
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It offers an interface for easy model integration and testing and a protocol for comparing different audio tokenizers.
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Pooneh Mousavi, Luca Della Libera, Jarod Duret, Arten Ploujnikov, Cem Subakan, Mirco Ravanelli,
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<em>DASB - Discrete Audio and Speech Benchmark</em>, 2024
@@ -118,6 +119,7 @@ <h2> 📊 Available Benchmarks</h2>
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Luca Della Libera, Pooneh Mousavi, Salah Zaiem, Cem Subakan, Mirco Ravanelli, (2024). CL-MASR: A continual learning benchmark for multilingual ASR. <i>IEEE/ACM Transactions on Audio, Speech, and Language Processing, 32</i>, 4931–4944.
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