We present a scalable and efficient neural waveform coding system for speech
compression. We formulate the speech coding problem as an autoencoding task, where a …

Scalability and efficiency are desired in neural speech codecs, which supports a wide range
of bitrates for applications on various devices. We propose a collaborative quantization (CQ) …

Neural audio/speech coding has recently demonstrated its capability to deliver high quality
at much lower bitrates than traditional methods. However, existing neural audio/speech …

This paper introduces a novel neural network-based speech coding system that can process
noisy speech effectively. The proposed source-aware neural audio coding (SANAC) system …

Neural networks have proven to be a formidable tool to tackle the problem of speech coding
at very low bit rates. However, the design of a neural coder that can be operated robustly …

Neural speech codec has recently gained widespread attention in generative speech
modeling domains, like voice conversion, text-to-speech synthesis, etc. However, ensuring …

Speech coding facilitates the transmission of speech over low-bandwidth networks with
minimal distortion. Neural-network based speech codecs have recently demonstrated …

Recently, speech codecs based on neural networks have proven to perform better than
traditional methods. However, redundancy in traditional parameter quantization is visible …

Recently, neural networks have proven to be effective in performing speech coding task at
low bitrates. However, under-utilization of intra-frame correlations and the error of quantizer …

We propose a novel neural waveform compression method to catalyze emerging speech
semantic communications. By introducing nonlinear transform and variational modeling, we …