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Found 11 papers, 3 papers with code
Improving End-to-End Speech Processing by Efficient Text Data Utilization with Latent Synthesis
For SLU, LaSyn improves our E2E baseline by absolute 4. 1% for intent classification accuracy and 3. 8% for slot filling SLU-F1 on SLURP, and absolute 4. 49% and 2. 25% for exact match (EM) and EM-Tree accuracies on STOP respectively.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
CorrectSpeech: A Fully Automated System for Speech Correction and Accent Reduction
This study propose a fully automated system for speech correction and accent reduction.
Reducing language context confusion for end-to-end code-switching automatic speech recognition
We propose a language-related attention mechanism to reduce multilingual context confusion for the E2E code-switching ASR model based on the Equivalence Constraint (EC) Theory.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
SPIRAL: Self-supervised Perturbation-Invariant Representation Learning for Speech Pre-Training
The student network is trained to output representation resembling that of the teacher.
CoCA-MDD: A Coupled Cross-Attention based Framework for Streaming Mispronunciation Detection and Diagnosis
We utilize conv-transformer structure to encode input speech in a streaming manner.
EditSpeech: A Text Based Speech Editing System Using Partial Inference and Bidirectional Fusion
This paper presents the design, implementation and evaluation of a speech editing system, named EditSpeech, which allows a user to perform deletion, insertion and replacement of words in a given speech utterance, without causing audible degradation in speech quality and naturalness.
VQMIVC: Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion
One-shot voice conversion (VC), which performs conversion across arbitrary speakers with only a single target-speaker utterance for reference, can be effectively achieved by speech representation disentanglement.
Unsupervised Domain Adaptation for Dysarthric Speech Detection via Domain Adversarial Training and Mutual Information Minimization
Such systems are particularly susceptible to domain mismatch where the training and testing data come from the source and target domains respectively, but the two domains may differ in terms of speech stimuli, disease etiology, etc.
The HUAWEI Speaker Diarisation System for the VoxCeleb Speaker Diarisation Challenge
This paper describes system setup of our submission to speaker diarisation track (Track 4) of VoxCeleb Speaker Recognition Challenge 2020.
Conv-Transformer Transducer: Low Latency, Low Frame Rate, Streamable End-to-End Speech Recognition
To reduce computation cost, we gradually downsample acoustic input, also with the interleaved convolution layers.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
