awesome-asr-contextualization
github.com/stevenhillis/awesome-asr-contextualization ↗A curated list of awesome papers on contextualizing E2E ASR outputs
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GitHub Stars
43
Curated Resources
2
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22 hours ago
Last Refreshed
Deep ContextualizationExternal Contextualization
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me 2021 resources from awesome-asr-contextualization"
Installation instructions →What's inside
External Contextualization
- A Light-weight contextual spelling correction model for customizing transducer-based speech recognition systems2021
- A Specialized WFST Approach for Class Models and Dynamic Vocabulary2012
- Bangla Voice Command Recognition in end-to-end System Using Topic Modeling based Contextual Rescoring2019
- Class LM and word mapping for contextual biasing in End-to-End ASR2019
- Composition-based on-the-fly rescoring for salient n-gram biasing2015
- Contextualizing ASR Lattice Rescoring with Hybrid Pointer Network Language Model2019
Deep Contextualization
- Context-Aware Transformer Transducer for Speech RecognitionContextual Transducer ("RNNTs")
- Contextual Adapters for Personalized Speech Recognition in Neural TransducersContextual Transducer ("RNNTs")
- Contextualized Streaming End-to-End Speech Recognition with Trie-Based Deep Biasing and Shallow FusionContextual Transducer ("RNNTs")
- Contextual RNN-T For Open Domain ASRContextual Transducer ("RNNTs")
- Contextual Speech Recognition with Difficult Negative Training ExamplesContextual LAS (CLAS)
- Deep context: end-to-end contextual speech recognitionContextual LAS (CLAS)
Showing a sample of 43 resources. View the full list on GitHub →