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09/15/2023
Mixture Encoder Supporting Continuous Speech Separation for Meeting Recognition
Many real-life applications of automatic speech recognition (ASR) requir...
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09/15/2023
Chunked Attention-based Encoder-Decoder Model for Streaming Speech Recognition
We study a streamable attention-based encoder-decoder model in which eit...
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08/08/2023
Comparative Analysis of the wav2vec 2.0 Feature Extractor
Automatic speech recognition (ASR) systems typically use handcrafted fea...
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06/21/2023
Mixture Encoder for Joint Speech Separation and Recognition
Multi-speaker automatic speech recognition (ASR) is crucial for many rea...
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06/15/2023
Competitive and Resource Efficient Factored Hybrid HMM Systems are Simpler Than You Think
Building competitive hybrid hidden Markov model (HMM) systems for automa...
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05/28/2023
RASR2: The RWTH ASR Toolkit for Generic Sequence-to-sequence Speech Recognition
Modern public ASR tools usually provide rich support for training variou...
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03/03/2023
End-to-End Speech Recognition: A Survey
In the last decade of automatic speech recognition (ASR) research, the i...
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01/11/2023
Improving And Analyzing Neural Speaker Embeddings for ASR
Neural speaker embeddings encode the speaker's speech characteristics th...
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12/07/2022
Lattice-Free Sequence Discriminative Training for Phoneme-Based Neural Transducers
Recently, RNN-Transducers have achieved remarkable results on various au...
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10/26/2022
Efficient Use of Large Pre-Trained Models for Low Resource ASR
Automatic speech recognition (ASR) has been established as a well-perfor...
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10/26/2022
Monotonic segmental attention for automatic speech recognition
We introduce a novel segmental-attention model for automatic speech reco...
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10/24/2022
Development of Hybrid ASR Systems for Low Resource Medical Domain Conversational Telephone Speech
Language barriers present a great challenge in our increasingly connecte...
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10/18/2022
HMM vs. CTC for Automatic Speech Recognition: Comparison Based on Full-Sum Training from Scratch
In this work, we compare from-scratch sequence-level cross-entropy (full...
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06/26/2022
Improving the Training Recipe for a Robust Conformer-based Hybrid Model
Speaker adaptation is important to build robust automatic speech recogni...
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04/22/2022
Efficient Training of Neural Transducer for Speech Recognition
As one of the most popular sequence-to-sequence modeling approaches for ...
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01/24/2022
Improving Factored Hybrid HMM Acoustic Modeling without State Tying
In this work, we show that a factored hybrid hidden Markov model (FH-HMM...
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11/13/2021
Prediction of Listener Perception of Argumentative Speech in a Crowdsourced Dataset Using (Psycho-)Linguistic and Fluency Features
One of the key communicative competencies is the ability to maintain flu...
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11/11/2021
Self-Normalized Importance Sampling for Neural Language Modeling
To mitigate the problem of having to traverse over the full vocabulary i...
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11/05/2021
Conformer-based Hybrid ASR System for Switchboard Dataset
The recently proposed conformer architecture has been successfully used ...
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10/18/2021
Automatic Learning of Subword Dependent Model Scales
To improve the performance of state-of-the-art automatic speech recognit...
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10/18/2021
Efficient Sequence Training of Attention Models using Approximative Recombination
Sequence discriminative training is a great tool to improve the performa...
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10/13/2021
On Language Model Integration for RNN Transducer based Speech Recognition
The mismatch between an external language model (LM) and the implicitly ...
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05/31/2021
Why does CTC result in peaky behavior?
The peaky behavior of CTC models is well known experimentally. However, ...
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04/21/2021
On Sampling-Based Training Criteria for Neural Language Modeling
As the vocabulary size of modern word-based language models becomes ever...
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04/19/2021
Acoustic Data-Driven Subword Modeling for End-to-End Speech Recognition
Subword units are commonly used for end-to-end automatic speech recognit...
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04/17/2021
The Impact of ASR on the Automatic Analysis of Linguistic Complexity and Sophistication in Spontaneous L2 Speech
In recent years, automated approaches to assessing linguistic complexity...
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04/13/2021
Equivalence of Segmental and Neural Transducer Modeling: A Proof of Concept
With the advent of direct models in automatic speech recognition (ASR), ...
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04/12/2021
Investigating Methods to Improve Language Model Integration for Attention-based Encoder-Decoder ASR Models
Attention-based encoder-decoder (AED) models learn an implicit internal ...
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04/12/2021
Comparing the Benefit of Synthetic Training Data for Various Automatic Speech Recognition Architectures
Recent publications on automatic-speech-recognition (ASR) have a strong ...
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04/09/2021
Feature Replacement and Combination for Hybrid ASR Systems
Acoustic modeling of raw waveform and learning feature extractors as par...
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04/07/2021
Librispeech Transducer Model with Internal Language Model Prior Correction
We present our transducer model on Librispeech. We study variants to inc...
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04/06/2021
Towards Consistent Hybrid HMM Acoustic Modeling
High-performance hybrid automatic speech recognition (ASR) systems are o...
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03/30/2021
A study of latent monotonic attention variants
End-to-end models reach state-of-the-art performance for speech recognit...
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11/24/2020
Tight Integrated End-to-End Training for Cascaded Speech Translation
A cascaded speech translation model relies on discrete and non-different...
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10/30/2020
Phoneme Based Neural Transducer for Large Vocabulary Speech Recognition
To join the advantages of classical and end-to-end approaches for speech...
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05/20/2020
Investigation of Large-Margin Softmax in Neural Language Modeling
To encourage intra-class compactness and inter-class separability among ...
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05/20/2020
Early Stage LM Integration Using Local and Global Log-Linear Combination
Sequence-to-sequence models with an implicit alignment mechanism (e.g. a...
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05/19/2020
Investigations on Phoneme-Based End-To-End Speech Recognition
Common end-to-end models like CTC or encoder-decoder-attention models us...
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05/19/2020
A New Training Pipeline for an Improved Neural Transducer
The RNN transducer is a promising end-to-end model candidate. We compare...
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05/15/2020
Context-Dependent Acoustic Modeling without Explicit Phone Clustering
Phoneme-based acoustic modeling of large vocabulary automatic speech rec...
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04/02/2020
Full-Sum Decoding for Hybrid HMM based Speech Recognition using LSTM Language Model
In hybrid HMM based speech recognition, LSTM language models have been w...
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04/02/2020
The RWTH ASR System for TED-LIUM Release 2: Improving Hybrid HMM with SpecAugment
We present a complete training pipeline to build a state-of-the-art hybr...
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12/19/2019
Generating Synthetic Audio Data for Attention-Based Speech Recognition Systems
Recent advances in text-to-speech (TTS) led to the development of flexib...
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11/20/2019
On using 2D sequence-to-sequence models for speech recognition
Attention-based sequence-to-sequence models have shown promising results...
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11/20/2019
On Using SpecAugment for End-to-End Speech Translation
This work investigates a simple data augmentation technique, SpecAugment...
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07/01/2019
LSTM Language Models for LVCSR in First-Pass Decoding and Lattice-Rescoring
LSTM based language models are an important part of modern LVCSR systems...
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07/01/2019
Comparison of Lattice-Free and Lattice-Based Sequence Discriminative Training Criteria for LVCSR
Sequence discriminative training criteria have long been a standard tool...
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06/14/2019
Cumulative Adaptation for BLSTM Acoustic Models
This paper addresses the robust speech recognition problem as an adaptat...
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05/10/2019
Language Modeling with Deep Transformers
We explore multi-layer autoregressive Transformer models in language mod...
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05/09/2019