task_path stringlengths 3 199 ⌀ | dataset stringlengths 1 128 ⌀ | model_name stringlengths 1 223 ⌀ | paper_url stringlengths 21 601 ⌀ | metric_name stringlengths 1 50 ⌀ | metric_value stringlengths 1 9.22k ⌀ |
|---|---|---|---|---|---|
Speech Recognition | LibriSpeech test-other | FAdam | https://arxiv.org/abs/2405.12807v10 | Word Error Rate (WER) | 2.49 |
Speech Recognition | LibriSpeech test-other | w2v-BERT XXL | https://arxiv.org/abs/2108.06209v2 | Word Error Rate (WER) | 2.5 |
Speech Recognition | LibriSpeech test-other | Conformer + Wav2vec 2.0 + SpecAugment-based Noisy Student Training with Libri-Light | https://arxiv.org/abs/2010.10504v2 | Word Error Rate (WER) | 2.6 |
Speech Recognition | LibriSpeech test-other | HuBERT with Libri-Light | https://arxiv.org/abs/2106.07447v1 | Word Error Rate (WER) | 2.9 |
Speech Recognition | LibriSpeech test-other | wav2vec 2.0 with Libri-Light | https://arxiv.org/abs/2006.11477v3 | Word Error Rate (WER) | 3.0 |
Speech Recognition | LibriSpeech test-other | Conv + Transformer + wav2vec2.0 + pseudo labeling | https://arxiv.org/abs/2010.11430v1 | Word Error Rate (WER) | 3.1 |
Speech Recognition | LibriSpeech test-other | WavLM Large | https://arxiv.org/abs/2110.13900v5 | Word Error Rate (WER) | 3.2 |
Speech Recognition | LibriSpeech test-other | SpeechStew (1B) | https://arxiv.org/abs/2104.02133v3 | Word Error Rate (WER) | 3.3 |
Speech Recognition | LibriSpeech test-other | ContextNet + SpecAugment-based Noisy Student Training with Libri-Light | https://arxiv.org/abs/2005.09629v2 | Word Error Rate (WER) | 3.4 |
Speech Recognition | LibriSpeech test-other | E-Branchformer (L) + Internal Language Model Estimation | https://arxiv.org/abs/2210.00077v2 | Word Error Rate (WER) | 3.65 |
Speech Recognition | LibriSpeech test-other | data2vec | https://arxiv.org/abs/2202.03555v3 | Word Error Rate (WER) | 3.7 |
Speech Recognition | LibriSpeech test-other | Conv + Transformer AM + Iterative Pseudo-Labeling (n-gram LM + Transformer Rescoring) | https://arxiv.org/abs/2005.09267v2 | Word Error Rate (WER) | 3.83 |
Speech Recognition | LibriSpeech test-other | Conformer(L) | https://arxiv.org/abs/2005.08100v1 | Word Error Rate (WER) | 3.9 |
Speech Recognition | LibriSpeech test-other | Zipformer+pruned transducer w/ CR-CTC
(no external language model) | https://arxiv.org/abs/2410.05101v4 | Word Error Rate (WER) | 3.95 |
Speech Recognition | LibriSpeech test-other | SpeechStew (100M) | https://arxiv.org/abs/2104.02133v3 | Word Error Rate (WER) | 4.0 |
Speech Recognition | LibriSpeech test-other | wav2vec 2.0 | https://arxiv.org/abs/2006.11477v3 | Word Error Rate (WER) | 4.1 |
Speech Recognition | LibriSpeech test-other | ContextNet(L) | https://arxiv.org/abs/2005.03191v3 | Word Error Rate (WER) | 4.1 |
Speech Recognition | LibriSpeech test-other | Conv + Transformer AM (ConvLM with Transformer Rescoring) | https://arxiv.org/abs/1911.08460v3 | Word Error Rate (WER) | 4.11 |
Speech Recognition | LibriSpeech test-other | CTC + Transformer LM rescoring | https://arxiv.org/abs/2005.09150v2 | Word Error Rate (WER) | 4.20 |
Speech Recognition | LibriSpeech test-other | Transformer Transducer | https://arxiv.org/abs/2011.03109v2 | Word Error Rate (WER) | 4.20 |
Speech Recognition | LibriSpeech test-other | Qwen-Audio | https://arxiv.org/abs/2311.07919v2 | Word Error Rate (WER) | 4.2 |
Speech Recognition | LibriSpeech test-other | Conformer(M) | https://arxiv.org/abs/2005.08100v1 | Word Error Rate (WER) | 4.3 |
Speech Recognition | LibriSpeech test-other | Zipformer+CR-CTC
(no external language model) | https://arxiv.org/abs/2410.05101v4 | Word Error Rate (WER) | 4.35 |
Speech Recognition | LibriSpeech test-other | Zipformer+pruned transducer
(no external language model) | https://arxiv.org/abs/2310.11230v4 | Word Error Rate (WER) | 4.38 |
Speech Recognition | LibriSpeech test-other | Multistream CNN with Self-Attentive SRU | https://arxiv.org/abs/2005.10469v1 | Word Error Rate (WER) | 4.46 |
Speech Recognition | LibriSpeech test-other | ContextNet(M) | https://arxiv.org/abs/2005.03191v3 | Word Error Rate (WER) | 4.5 |
Speech Recognition | LibriSpeech test-other | hybrid + Transformer LM rescoring | https://arxiv.org/abs/1910.09799v2 | Word Error Rate (WER) | 4.85 |
Speech Recognition | LibriSpeech test-other | Branchformer + GFSA | https://arxiv.org/abs/2312.04234v5 | Word Error Rate (WER) | 4.94 |
Speech Recognition | LibriSpeech test-other | Hybrid model with Transformer rescoring | https://arxiv.org/abs/1905.03072v3 | Word Error Rate (WER) | 5.0 |
Speech Recognition | LibriSpeech test-other | Conformer(S) | https://arxiv.org/abs/2005.08100v1 | Word Error Rate (WER) | 5.0 |
Speech Recognition | LibriSpeech test-other | Conv + Transformer AM (ConvLM with Transformer Rescoring) (LS only) | https://arxiv.org/abs/1911.08460v3 | Word Error Rate (WER) | 5.18 |
Speech Recognition | LibriSpeech test-other | ContextNet(S) | https://arxiv.org/abs/2005.03191v3 | Word Error Rate (WER) | 5.5 |
Speech Recognition | LibriSpeech test-other | LSTM Transducer | https://arxiv.org/abs/2104.03006v2 | Word Error Rate (WER) | 5.6 |
Speech Recognition | LibriSpeech test-other | Transformer | https://arxiv.org/abs/1909.06317v2 | Word Error Rate (WER) | 5.7 |
Speech Recognition | LibriSpeech test-other | LAS + SpecAugment | https://arxiv.org/abs/1904.08779v3 | Word Error Rate (WER) | 5.8 |
Speech Recognition | LibriSpeech test-other | Multi-Stream Self-Attention With Dilated 1D Convolutions | https://arxiv.org/abs/1910.00716v1 | Word Error Rate (WER) | 5.80 |
Speech Recognition | LibriSpeech test-other | Squeezeformer (L) | https://arxiv.org/abs/2206.00888v2 | Word Error Rate (WER) | 5.97 |
Speech Recognition | LibriSpeech test-other | LAS (no LM) | https://arxiv.org/abs/1904.08779v3 | Word Error Rate (WER) | 6.5 |
Speech Recognition | LibriSpeech test-other | Conformer with Relaxed Attention | https://arxiv.org/abs/2107.01275v2 | Word Error Rate (WER) | 6.85 |
Speech Recognition | LibriSpeech test-other | QuartzNet15x5 | https://arxiv.org/abs/1910.10261v1 | Word Error Rate (WER) | 7.25 |
Speech Recognition | LibriSpeech test-other | tdnn + chain + rnnlm rescoring | https://www.cs.jhu.edu/~hxu/neural-network-language.pdf | Word Error Rate (WER) | 7.63 |
Speech Recognition | LibriSpeech test-other | Jasper DR 10x5 (+ Time/Freq Masks) | https://arxiv.org/abs/1904.03288v3 | Word Error Rate (WER) | 7.84 |
Speech Recognition | LibriSpeech test-other | Espresso | https://arxiv.org/abs/1909.08723v3 | Word Error Rate (WER) | 8.7 |
Speech Recognition | LibriSpeech test-other | Jasper DR 10x5 | https://arxiv.org/abs/1904.03288v3 | Word Error Rate (WER) | 8.79 |
Speech Recognition | LibriSpeech test-other | MT4SSL | https://arxiv.org/abs/2211.07321v3 | Word Error Rate (WER) | 9.6 |
Speech Recognition | LibriSpeech test-other | Convolutional Speech Recognition | http://arxiv.org/abs/1812.06864v2 | Word Error Rate (WER) | 10.47 |
Speech Recognition | LibriSpeech test-other | CTC-CRF 4gram-LM | https://ieeexplore.ieee.org/document/8682256 | Word Error Rate (WER) | 10.65 |
Speech Recognition | LibriSpeech test-other | TDNN + pNorm + speed up/down speech | null | Word Error Rate (WER) | 12.5 |
Speech Recognition | LibriSpeech test-other | Deep Speech 2 | http://arxiv.org/abs/1512.02595v1 | Word Error Rate (WER) | 13.25 |
Speech Recognition | LibriSpeech test-other | Local Prior Matching (Large Model, ConvLM LM) | https://arxiv.org/abs/2002.10336v1 | Word Error Rate (WER) | 15.28 |
Speech Recognition | LibriSpeech test-other | Snips | http://arxiv.org/abs/1805.10190v3 | Word Error Rate (WER) | 16.5 |
Speech Recognition | LibriSpeech test-other | Local Prior Matching (Large Model) | https://arxiv.org/abs/2002.10336v1 | Word Error Rate (WER) | 20.84 |
Speech Recognition | Common Voice Russian | Whisper (Large v2) | https://arxiv.org/abs/2212.04356v1 | Test WER | 7.1% |
Speech Recognition | Common Voice Spanish | ConformerCTC-L (4-gram) | https://arxiv.org/abs/1909.09577v1 | Test WER | 5.5% |
Speech Recognition | Common Voice Spanish | Whisper (Large v2) | https://arxiv.org/abs/2212.04356v1 | Test WER | 5.6% |
Speech Recognition | Common Voice Spanish | ConformerCTC-L (5-gram) | https://arxiv.org/abs/2110.07982v1 | Test WER | 5.68% |
Speech Recognition | Common Voice Spanish | ConformerCTC-L (no LM) | https://arxiv.org/abs/1909.09577v1 | Test WER | 6.9% |
Speech Recognition | Common Voice Spanish | ConformerCTC-L (no-LM) | https://arxiv.org/abs/2110.07982v1 | Test WER | 7.46 % |
Speech Recognition | Common Voice Spanish | QuartzNet15x5ES (D8) | https://arxiv.org/abs/2110.07982v1 | Test WER | 10.0% |
Speech Recognition | Common Voice Spanish | VoxPopuli-50K (n-gram) | https://arxiv.org/abs/2101.00390v2 | Test WER | 10.0% |
Speech Recognition | Common Voice Spanish | QuartzNet15x5ES (CV-only) | https://arxiv.org/abs/2110.07982v1 | Test WER | 10.5% |
Speech Recognition | Switchboard (300hr) | End-to-end LF-MMI | https://www.isca-speech.org/archive/Interspeech_2018/abstracts/1423.html | Word Error Rate (WER) | 9.3 |
Speech Recognition | VIVOS | khanhld/chunkformer-large-vie | https://arxiv.org/abs/2502.14673v1 | Test WER | 4.18 |
Speech Recognition | VIVOS | Vietnamese end-to-end speech recognition using wav2vec 2.0 by VietAI | https://github.com/vietai/ASR | Test WER | 6.15 |
Speech Recognition | VIVOS | wav2vec2-base-vietnamese-160h (No Language Model) | https://huggingface.co/khanhld/wav2vec2-base-vietnamese-160h | Test WER | 15.05 |
Speech Recognition | AISHELL-1 | FireRedASR-AED | https://arxiv.org/abs/2501.14350v1 | Word Error Rate (WER) | 0.55 |
Speech Recognition | AISHELL-1 | FireRedASR-AED | https://arxiv.org/abs/2501.14350v1 | Params(M) | 1,100 |
Speech Recognition | AISHELL-1 | Seed-ASR | https://arxiv.org/abs/2407.04675v2 | Word Error Rate (WER) | 0.68 |
Speech Recognition | AISHELL-1 | Qwen-Audio | https://arxiv.org/abs/2311.07919v2 | Word Error Rate (WER) | 1.29 |
Speech Recognition | AISHELL-1 | MMSpeech With LM | https://arxiv.org/abs/2212.00500v1 | Word Error Rate (WER) | 1.9 |
Speech Recognition | AISHELL-1 | Paraformer-large | https://arxiv.org/abs/2305.11013v1 | Word Error Rate (WER) | 1.95 |
Speech Recognition | AISHELL-1 | Paraformer-large | https://arxiv.org/abs/2305.11013v1 | Params(M) | 220 |
Speech Recognition | AISHELL-1 | Zipformer+CR-CTC (no external language model) | https://arxiv.org/abs/2410.05101v4 | Word Error Rate (WER) | 4.02 |
Speech Recognition | AISHELL-1 | Zipformer+CR-CTC (no external language model) | https://arxiv.org/abs/2410.05101v4 | Params(M) | 66.2 |
Speech Recognition | AISHELL-1 | Lightweight Transducer With LM | https://arxiv.org/abs/2409.13698v2 | Word Error Rate (WER) | 4.03 |
Speech Recognition | AISHELL-1 | Lightweight Transducer With LM | https://arxiv.org/abs/2409.13698v2 | Params(M) | 45.3 |
Speech Recognition | AISHELL-1 | SE-WSBO With LM | https://arxiv.org/abs/2207.11697v5 | Word Error Rate (WER) | 4.1 |
Speech Recognition | AISHELL-1 | SE-WSBO With LM | https://arxiv.org/abs/2207.11697v5 | Params(M) | 46 |
Speech Recognition | AISHELL-1 | CIF-HKD With LM | https://arxiv.org/abs/2301.13003v2 | Word Error Rate (WER) | 4.1 |
Speech Recognition | AISHELL-1 | CIF-HKD With LM | https://arxiv.org/abs/2301.13003v2 | Params(M) | 47 |
Speech Recognition | AISHELL-1 | Lightweight Transducer | https://arxiv.org/abs/2409.13698v2 | Word Error Rate (WER) | 4.31 |
Speech Recognition | AISHELL-1 | Lightweight Transducer | https://arxiv.org/abs/2409.13698v2 | Params(M) | 45.3 |
Speech Recognition | AISHELL-1 | UMA | https://arxiv.org/abs/2309.08150v2 | Word Error Rate (WER) | 4.7 |
Speech Recognition | AISHELL-1 | UMA | https://arxiv.org/abs/2309.08150v2 | Params(M) | 44.7 |
Speech Recognition | AISHELL-1 | U2 | https://arxiv.org/abs/2012.05481v2 | Word Error Rate (WER) | 4.72 |
Speech Recognition | AISHELL-1 | U2 | https://arxiv.org/abs/2012.05481v2 | Params(M) | 47 |
Speech Recognition | AISHELL-1 | Paraformer | https://arxiv.org/abs/2305.11013v1 | Word Error Rate (WER) | 4.95 |
Speech Recognition | AISHELL-1 | Paraformer | https://arxiv.org/abs/2305.11013v1 | Params(M) | 46.3 |
Speech Recognition | AISHELL-1 | BAT | https://arxiv.org/abs/2305.11571v1 | Word Error Rate (WER) | 4.97 |
Speech Recognition | AISHELL-1 | BAT | https://arxiv.org/abs/2305.11571v1 | Params(M) | 90 |
Speech Recognition | AISHELL-1 | CTC-CRF 4gram-LM | https://arxiv.org/abs/2005.13326v2 | Word Error Rate (WER) | 6.34 |
Speech Recognition | AISHELL-1 | BRA-E | https://arxiv.org/abs/2303.13072v2 | Word Error Rate (WER) | 6.63 |
Speech Recognition | AISHELL-1 | BRA-E | https://arxiv.org/abs/2303.13072v2 | Params(M) | 8.5 |
Speech Recognition | AISHELL-1 | CTC/Att | https://arxiv.org/abs/1909.06317v2 | Word Error Rate (WER) | 6.7 |
Speech Recognition | AISHELL-1 | Att | http://arxiv.org/abs/1808.10088v2 | Word Error Rate (WER) | 18.7 |
Speech Recognition | Common Voice Portuguese | XLSR53 Wav2Vec2 Portuguese by Orlem Santos | https://github.com/Orlllem/wav2vec2-fairseq-pt-br | Test WER | 10.74% |
Speech Recognition | Common Voice French | ConformerCTC-L (5-gram) | https://arxiv.org/abs/2110.07982v1 | Test WER | 8.13% |
Speech Recognition | Common Voice French | ConformerCTC-L (4-gram) | https://arxiv.org/abs/1909.09577v1 | Test WER | 9.16% |
Speech Recognition | Common Voice French | VoxPopuli-50K (n-gram) | https://arxiv.org/abs/2101.00390v2 | Test WER | 9.6% |
Speech Recognition | Common Voice French | ConformerCTC-L (no-LM) | https://arxiv.org/abs/1909.09577v1 | Test WER | 9.63% |
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