# Using Text Injection to Improve Recognition of Personal Identifiers in Speech

arXiv: https://arxiv.org/abs/2308.07393 · HTML: https://mlsanity.com/paper/2308.07393/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 24 references that are in the map.
- First posted on arXiv 14 Aug 2023.

## Builds on (most cited first, 14 of 14)

- [Hybrid Autoregressive Transducer (hat)](https://mlsanity.com/paper/2003.07705/) (2020)
- [mSLAM: Massively multilingual joint pre-training for speech and text](https://mlsanity.com/paper/2202.01374/) (2022)
- [SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network](https://mlsanity.com/paper/2104.02133/) (2021)
- [MAESTRO: Matched Speech Text Representations through Modality Matching](https://mlsanity.com/paper/2204.03409/) (2022)
- [Recognizing long-form speech using streaming end-to-end models](https://mlsanity.com/paper/1910.11455/) (2019)
- [Speech Recognition with Augmented Synthesized Speech](https://mlsanity.com/paper/1909.11699/) (2019)
- [Parallel Tacotron: Non-Autoregressive and Controllable TTS](https://mlsanity.com/paper/2010.11439/) (2020)
- [ASR Error Correction and Domain Adaptation Using Machine Translation](https://mlsanity.com/paper/2003.07692/) (2020)
- [Using Synthetic Audio to Improve The Recognition of Out-Of-Vocabulary Words in End-To-End ASR Systems](https://mlsanity.com/paper/2011.11564/) (2020)
- [SynthASR: Unlocking Synthetic Data for Speech Recognition](https://mlsanity.com/paper/2106.07803/) (2021)
- [JOIST: A Joint Speech and Text Streaming Model For ASR](https://mlsanity.com/paper/2210.07353/) (2022)
- [Integrating Text Inputs For Training and Adapting RNN Transducer ASR Models](https://mlsanity.com/paper/2202.13155/) (2022)
- [Speech recognition for medical conversations](https://mlsanity.com/paper/1711.07274/) (2017)
- [Understanding Shared Speech-Text Representations](https://mlsanity.com/paper/2304.14514/) (2023)

## Built on by (most cited first, 3 of 3)

- [Recovering from Privacy-Preserving Masking with Large Language Models](https://mlsanity.com/paper/2309.08628/) (2023)
- [Enhancing Multilingual Voice Toxicity Detection with Speech-Text Alignment](https://mlsanity.com/paper/2406.10325/) (2024)
- [ASTRA: Aligning Speech and Text Representations for Asr without Sampling](https://mlsanity.com/paper/2406.06664/) (2024)

## Abstract (arXiv)

Accurate recognition of specific categories, such as persons' names, dates or other identifiers is critical in many Automatic Speech Recognition (ASR) applications. As these categories represent personal information, ethical use of this data including collection, transcription, training and evaluation demands special care. One way of ensuring the security and privacy of individuals is to redact or eliminate Personally Identifiable Information (PII) from collection altogether. However, this results in ASR models that tend to have lower recognition accuracy of these categories. We use text-injection to improve the recognition of PII categories by including fake textual substitutes of PII categories in the training data using a text injection method. We demonstrate substantial improvement to Recall of Names and Dates in medical notes while improving overall WER. For alphanumeric digit sequences we show improvements to Character Error Rate and Sentence Accuracy.