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@@ -74,6 +74,7 @@ <h2> 📊 Available Benchmarks</h2>
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The following benchmarks are currently available:
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</p>
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<br>
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<hr class="separation-line">
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<a href="https://github.com/speechbrain/benchmarks/tree/main/benchmarks/MOABB" target="_blank">
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<img src="img/benchmarks/sb-moabb-logo.svg" alt="SpeechBrain-MOABB Logo" style="width: 500px; vertical-align: middle; margin-right: 100px;">
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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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<br><br>
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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
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arXiv preprint arXiv:2406.14294.
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<a href="https://arxiv.org/abs/2406.14294" target="_blank">[Paper]
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<br><br>
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<hr class="separation-line">
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<p class="justified large"> <a href="https://github.com/speechbrain/benchmarks/tree/main/benchmarks/CL_MASR" target="_blank">CL-MASR</a>
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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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<a href="https://arxiv.org/abs/2310.16931" target="_blank">[Paper]
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<p class="justified large"> <a href="https://github.com/speechbrain/benchmarks/tree/main/benchmarks/MP3S" target="_blank">MP23 - Multi-probe Speech Self Supervision Benchmark</a> aims to evaluate self-supervised representations on various downstream tasks, including <i>ASR</i>, <i>speaker verification</i>, <i>emotion recognition</i>, and <i>intent classification</i>.
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Salah Zaiem, Youcef Kemiche, Titouan Parcollet, Slim Essid, Mirco Ravanelli, (2023). Speech self-supervised representations benchmarking: a case for larger probing heads. <i>Computer Speech & Language, 89</i>, 101695.</i>
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<a href="https://www.sciencedirect.com/science/article/pii/S0885230824000780" target="_blank">[Paper]
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<br><br>
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</section>

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