10 citations · 18 across the 18 of their papers we have counts for
5 papers · 1 filter
Conformer-based Hybrid ASR System for Switchboard Dataset
Mohammad Zeineldeen, Jingjing Xu, Christoph Lüscher +4
The recently proposed conformer architecture has been successfully used for end-to-end automatic speech recognition (ASR) architectures achieving state-of-the-art performance on di…
Automatic Learning of Subword Dependent Model Scales
Felix Meyer, Wilfried Michel, Mohammad Zeineldeen +2
To improve the performance of state-of-the-art automatic speech recognition systems it is common practice to include external knowledge sources such as language models or prior cor…
Acoustic Data-Driven Subword Modeling for End-to-End Speech Recognition
Wei Zhou, Mohammad Zeineldeen, Zuoyun Zheng +2
Subword units are commonly used for end-to-end automatic speech recognition (ASR), while a fully acoustic-oriented subword modeling approach is somewhat missing. We propose an acou…
Investigating Methods to Improve Language Model Integration for Attention-based Encoder-Decoder ASR Models
Mohammad Zeineldeen, Aleksandr Glushko, Wilfried Michel +3
Attention-based encoder-decoder (AED) models learn an implicit internal language model (ILM) from the training transcriptions. The integration with an external LM trained on much m…
Comparing the Benefit of Synthetic Training Data for Various Automatic Speech Recognition Architectures
Nick Rossenbach, Mohammad Zeineldeen, Benedikt Hilmes +2
Recent publications on automatic-speech-recognition (ASR) have a strong focus on attention encoder-decoder (AED) architectures which tend to suffer from over-fitting in low resourc…