{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/wenet-2-0-more-productive-end-to-end-speech","title":"WeNet 2.0: More Productive End-to-End Speech Recognition Toolkit","arxiv_id":"2203.15455","date":"2022-03-29","proceeding":null,"authors":["BinBin Zhang","Di wu","Zhendong Peng","Xingchen Song","Zhuoyuan Yao","Hang Lv","Lei Xie","Chao Yang","Fuping Pan","Jianwei Niu"],"abstract":"Recently, we made available WeNet, a production-oriented end-to-end speech recognition toolkit, which introduces a unified two-pass (U2) framework and a built-in runtime to address the streaming and non-streaming decoding modes in a single model. To further improve ASR performance and facilitate various production requirements, in this paper, we present WeNet 2.0 with four important updates. (1) We propose U2++, a unified two-pass framework with bidirectional attention decoders, which includes the future contextual information by a right-to-left attention decoder to improve the representative ability of the shared encoder and the performance during the rescoring stage. (2) We introduce an n-gram based language model and a WFST-based decoder into WeNet 2.0, promoting the use of rich text data in production scenarios. (3) We design a unified contextual biasing framework, which leverages user-specific context (e.g., contact lists) to provide rapid adaptation ability for production and improves ASR accuracy in both with-LM and without-LM scenarios. (4) We design a unified IO to support large-scale data for effective model training. In summary, the brand-new WeNet 2.0 achieves up to 10\\% relative recognition performance improvement over the original WeNet on various corpora and makes available several important production-oriented features.","url_abs":"https://arxiv.org/abs/2203.15455v2","url_pdf":"https://arxiv.org/pdf/2203.15455v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"wenet-2-0-more-productive-end-to-end-speech","repo_url":"https://github.com/wenet-e2e/wenet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"wenet-2-0-more-productive-end-to-end-speech","repo_url":"https://github.com/leonwlw/wenet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"wenet-2-0-more-productive-end-to-end-speech","repo_url":"https://github.com/mobvoi/wenet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"speech-recognition","task_name":"Speech Recognition"},{"task_slug":"speech-recognition-1","task_name":"speech-recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2203.15455","atlas_url":"https://app.syntology.ai/?focus=2203.15455","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.15455"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/wenet-e2e/wenet","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/leonwlw/wenet","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/mobvoi/wenet","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"ran":10},"by_repo_kind":{"listed":{"samples":10,"ran":10,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"7a8bbc760099542d","entry":"amp2db","repo":"leonwlw/wenet","repo_kind":"listed","path":"wenet/dataset/wav_distortion.py","file_url":"https://github.com/leonwlw/wenet/blob/HEAD/wenet/dataset/wav_distortion.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"7a8bbc760099542d"}},{"code_sha256_prefix":"f80d5ced1e019437","entry":"batch","repo":"leonwlw/wenet","repo_kind":"listed","path":"wenet/dataset/processor.py","file_url":"https://github.com/leonwlw/wenet/blob/HEAD/wenet/dataset/processor.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"f80d5ced1e019437"}},{"code_sha256_prefix":"2fc2bbe453a37ecd","entry":"db2amp","repo":"leonwlw/wenet","repo_kind":"listed","path":"wenet/dataset/wav_distortion.py","file_url":"https://github.com/leonwlw/wenet/blob/HEAD/wenet/dataset/wav_distortion.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"2fc2bbe453a37ecd"}},{"code_sha256_prefix":"2d01074c23bc90de","entry":"get_frames_timestamp","repo":"leonwlw/wenet","repo_kind":"listed","path":"wenet/bin/alignment.py","file_url":"https://github.com/leonwlw/wenet/blob/HEAD/wenet/bin/alignment.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"2d01074c23bc90de"}},{"code_sha256_prefix":"a7f9e384e3a3e16d","entry":"make_poly_distortion","repo":"leonwlw/wenet","repo_kind":"listed","path":"wenet/dataset/wav_distortion.py","file_url":"https://github.com/leonwlw/wenet/blob/HEAD/wenet/dataset/wav_distortion.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"a7f9e384e3a3e16d"}},{"code_sha256_prefix":"df07b4faa7609d90","entry":"open_or_fd","repo":"leonwlw/wenet","repo_kind":"listed","path":"wenet/dataset/kaldi_io.py","file_url":"https://github.com/leonwlw/wenet/blob/HEAD/wenet/dataset/kaldi_io.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"df07b4faa7609d90"}},{"code_sha256_prefix":"d9a4862872e34aad","entry":"popen","repo":"leonwlw/wenet","repo_kind":"listed","path":"wenet/dataset/kaldi_io.py","file_url":"https://github.com/leonwlw/wenet/blob/HEAD/wenet/dataset/kaldi_io.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"d9a4862872e34aad"}},{"code_sha256_prefix":"aa10e48fc468d9e0","entry":"read_key","repo":"leonwlw/wenet","repo_kind":"listed","path":"wenet/dataset/kaldi_io.py","file_url":"https://github.com/leonwlw/wenet/blob/HEAD/wenet/dataset/kaldi_io.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"aa10e48fc468d9e0"}},{"code_sha256_prefix":"0562154e6c98265d","entry":"to_numpy","repo":"leonwlw/wenet","repo_kind":"listed","path":"wenet/bin/export_onnx_cpu.py","file_url":"https://github.com/leonwlw/wenet/blob/HEAD/wenet/bin/export_onnx_cpu.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"0562154e6c98265d"}},{"code_sha256_prefix":"03a5062a6ac43d6d","entry":"to_numpy","repo":"leonwlw/wenet","repo_kind":"listed","path":"wenet/bin/export_onnx_gpu.py","file_url":"https://github.com/leonwlw/wenet/blob/HEAD/wenet/bin/export_onnx_gpu.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"03a5062a6ac43d6d"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}