6 citations · 22 across the 8 of their papers we have counts for
8 papers
E-Branchformer: Branchformer with Enhanced merging for speech recognition
Kwangyoun Kim, Felix Wu, Yifan Peng +4
Conformer, combining convolution and self-attention sequentially to capture both local and global information, has shown remarkable performance and is currently regarded as the sta…
SRU++: Pioneering Fast Recurrence with Attention for Speech Recognition
Jing Pan, Tao Lei, Kwangyoun Kim +2
The Transformer architecture has been well adopted as a dominant architecture in most sequence transduction tasks including automatic speech recognition (ASR), since its attention…
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition
Felix Wu, Kwangyoun Kim, Jing Pan +3
This paper is a study of performance-efficiency trade-offs in pre-trained models for automatic speech recognition (ASR). We focus on wav2vec 2.0, and formalize several architecture…
Leveraging Pre-trained Language Model for Speech Sentiment Analysis
Suwon Shon, Pablo Brusco, Jing Pan +2
In this paper, we explore the use of pre-trained language models to learn sentiment information of written texts for speech sentiment analysis. First, we investigate how useful a p…
ASAPP-ASR: Multistream CNN and Self-Attentive SRU for SOTA Speech Recognition
Jing Pan, Joshua Shapiro, Jeremy Wohlwend +3
In this paper we present state-of-the-art (SOTA) performance on the LibriSpeech corpus with two novel neural network architectures, a multistream CNN for acoustic modeling and a se…
Benchmark Tests of Convolutional Neural Network and Graph Convolutional Network on HorovodRunner Enabled Spark Clusters
Jing Pan, Wendao Liu, Jing Zhou
The freedom of fast iterations of distributed deep learning tasks is crucial for smaller companies to gain competitive advantages and market shares from big tech giants. HorovodRun…
Multistream CNN for Robust Acoustic Modeling
Kyu J. Han, Jing Pan, Venkata Krishna Naveen Tadala +2
This paper proposes multistream CNN, a novel neural network architecture for robust acoustic modeling in speech recognition tasks. The proposed architecture processes input speech…
Order Matters at Fanatics Recommending Sequentially Ordered Products by LSTM Embedded with Word2Vec
Jing Pan, Weian Sheng, Santanu Dey
A unique challenge for e-commerce recommendation is that customers are often interested in products that are more advanced than their already purchased products, but not reversed.…