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Advancing Dysarthric Speech-to-Text Recognition with LATTE: A Low-Latency Acoustic Modeling Approach for Real-Time
Qurat Ul Ain1, Hammad Afzal1,2, Fazli Subhan3
1National University of Sciences & Technology (NUST), Islamabad, Pakistan.
Big Data
|February 9, 2026
Summary
This study introduces LATTE, a novel framework for real-time dysarthric speech recognition. It significantly improves the transcription accuracy of impaired speech, enhancing communication accessibility.
Area of Science:
- Speech and Hearing Sciences
- Artificial Intelligence
- Biomedical Engineering
Background:
- Dysarthria, a motor speech disorder, severely impacts communication.
- Conventional automatic speech recognition (ASR) systems struggle with dysarthric speech, especially in severe cases.
- A need exists for advanced ASR solutions tailored to impaired speech.
Purpose of the Study:
- To develop and evaluate a low-latency framework for real-time dysarthric speech recognition.
- To improve the accuracy and accessibility of ASR for individuals with dysarthria.
- To provide a robust foundation for digital applications and interactive environments handling impaired speech.
Main Methods:
- Introduction of the Low-Latency Acoustic Transcription and Textual Encoding (LATTE) framework.
- Integration of preprocessing, acoustic processing, and transcription mapping into a unified pipeline.
- Utilization of a hybrid architecture combining convolutional and bidirectional temporal layers for feature extraction and temporal dependency modeling.
Main Results:
- LATTE achieved a 12.5% word error rate (WER) on the UA-Speech dataset.
- Phoneme error rate (PER) was recorded at 8.3%, and character error rate (CER) at 1%.
- Demonstrated accurate, low-latency transcription of dysarthric speech.
Conclusions:
- LATTE offers a significant advancement in real-time ASR for dysarthric speech.
- The framework enhances communication and accessibility for individuals with speech impairments.
- LATTE provides a foundation for improved human-computer interaction in various applications.
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