Product code vector quantizers for waveform and voice coding

By M. Sabin, Robert M. Gray. 1984

Subfields: Speech & Audio, Information Theory

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Speech & Audio

1. Shankar Kumar
2. Ananda Theertha Suresh
3. Michael Nirschl
4. Felix X. Yu
5. Daniel Niels Holtmann-Rice
6. Tinku Acharya
7. Ping-Sing Tsai
8. Hank Liao

In Information Theory

1. Tinku Acharya
2. Felix X. Yu
3. Ping-Sing Tsai
4. Ananda Theertha Suresh

Citations in the corpus

• Introduction to Data Compression (2005, background): “Quantizers of this form are called gain-shape vector quantizers, or product code vector quantizers [133].”
• Lattice rescoring strategies for long short term memory language models in speech recognition (2017, methodology): “Product Quantization (PQ) [26] is a hybrid strategy that allows us to apply VQ in higher dimensions.”
• Author manuscript, published in "International Journal of Computer Vision (2013)" International Journal of Computer Vision manuscript No. (will be inserted by the editor) Image Classification with the Fisher Vector: Theory and Practice (2013, unknown): “as a first step towards gain/shape coding (Sabin and Gray, 1984), i.”