mlsanityData to 14 Oct 2026

An Effective, Performant Named Entity Recognition System for Noisy Business Telephone Conversation Transcripts

arXiv 2209.13736 ↗First posted 27 Sep 2022cs.CLcited by 7

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Abstract (arXiv)

We present a simple yet effective method to train a named entity recognition (NER) model that operates on business telephone conversation transcripts that contain noise due to the nature of spoken conversation and artifacts of automatic speech recognition. We first fine-tune LUKE, a state-of-the-art Named Entity Recognition (NER) model, on a limited amount of transcripts, then use it as the teacher model to teach a smaller DistilBERT-based student model using a large amount of weakly labeled data and a small amount of human-annotated data. The model achieves high accuracy while also satisfying the practical constraints for inclusion in a commercial telephony product: realtime performance when deployed on cost-effective CPUs rather than GPUs.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 13 of its 16 references that are in the map. First posted on arXiv 27 Sep 2022.

Builds on

13 of 16 references.

References · 13

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2015Distilling the Knowledge in a Neural Networkcited by 10,324
  3. 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,307
  4. 2020Knowledge Distillation: A Surveycited by 1,603
  5. 2015Bidirectional LSTM-CRF Models for Sequence Taggingcited by 546
  6. 2020LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attentioncited by 326
  7. 2018A Survey on Deep Learning for Named Entity Recognitioncited by 282
  8. 2019Distilling Task-Specific Knowledge from BERT into Simple Neural Networkscited by 153
  9. 2021Domain Adaptation with Pre-trained Transformers for Query Focused Abstractive Text Summarizationcited by 21
  10. 2019ner and pos when nothing is capitalizedcited by 15
  11. 2022BLINK with Elasticsearch for Efficient Entity Linking in Business Conversationscited by 13
  12. 2021Improving Punctuation Restoration for Speech Transcripts via External Datacited by 8
1 more
  1. 2022Developing a Production System for Purpose of Call Detection in Business Phone Conversationscited by 6

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Cited by year

Citing papers per year: 2022: 2; 2023: 3; 2024: 0; 2025: 2.

7 papers.

  1. 2023A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasetscited by 123
  2. 2023AI Coach Assist: An Automated Approach for Call Recommendation in Contact Centers for Agent Coachingcited by 8
  3. 2022Improving Named Entity Recognition in Telephone Conversations via Effective Active Learning with Human in the Loopcited by 7
  4. 2025AI Knowledge Assist: An Automated Approach for the Creation of Knowledge Bases for Conversational AI Agentscited by 5
  5. 2022Entity-level Sentiment Analysis in Contact Center Telephone Conversationscited by 4
  6. 2023Finite-context Indexing of Restricted Output Space for NLP Models Facing Noisy Inputcited by 0
  7. 2025Call2Instruct: Automated Pipeline for Generating Q&A Datasets from Call Center Recordings for LLM Fine-Tuningcited by 0