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Found 14 papers, 1 papers with code
Lookahead When It Matters: Adaptive Non-causal Transformers for Streaming Neural Transducers
Streaming speech recognition architectures are employed for low-latency, real-time applications.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Leveraging Redundancy in Multiple Audio Signals for Far-Field Speech Recognition
We augment the MC fusion networks to a conformer transducer model and train it in an end-to-end fashion.
A Method for Crash Prediction and Avoidance Using Hidden Markov Models
In particular, hidden Markov models are developed for the traffic lanes and speed change of vehicles on highway.
Toward Fairness in Speech Recognition: Discovery and mitigation of performance disparities
As for other forms of AI, speech recognition has recently been examined with respect to performance disparities across different user cohorts.
Reducing Geographic Disparities in Automatic Speech Recognition via Elastic Weight Consolidation
A popular approach is to fine-tune the model with data from regions where the ASR model has a higher word error rate (WER).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Compute Cost Amortized Transformer for Streaming ASR
We present a streaming, Transformer-based end-to-end automatic speech recognition (ASR) architecture which achieves efficient neural inference through compute cost amortization.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Investigation of Training Label Error Impact on RNN-T
In this paper, we propose an approach to quantitatively analyze impacts of different training label errors to RNN-T based ASR models.
Warped Dynamic Linear Models for Time Series of Counts
However, the options for count time series are limited: Gaussian DLMs require continuous data, while Poisson-based alternatives often lack sufficient modeling flexibility.
CoDERT: Distilling Encoder Representations with Co-learning for Transducer-based Speech Recognition
We find that tandem training of teacher and student encoders with an inplace encoder distillation outperforms the use of a pre-trained and static teacher transducer.
Do You Listen with One or Two Microphones? A Unified ASR Model for Single and Multi-Channel Audio
An ASR model that operates on both primary and auxiliary data can achieve better accuracy compared to a primary-only solution; and a model that can serve both primary-only (PO) and primary-plus-auxiliary (PPA) modes is highly desirable.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Attention-based Neural Beamforming Layers for Multi-channel Speech Recognition
The end-to-end 2D Conv-Attention model is compared with a multi-head self-attention and superdirective-based neural beamformers.
End-to-End Multi-Channel Transformer for Speech Recognition
Transformers are powerful neural architectures that allow integrating different modalities using attention mechanisms.
Global Inverse Design Across Multiple Photonic Structure Classes Using Generative Deep Learning
Understanding how nano- or micro-scale structures and material properties can be optimally configured to attain specific functionalities remains a fundamental challenge.
Optics
Multi-view Frequency LSTM: An Efficient Frontend for Automatic Speech Recognition
Acoustic models in real-time speech recognition systems typically stack multiple unidirectional LSTM layers to process the acoustic frames over time.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
