In this paper, we present a supervised graph-based framework for sequential processing and employ it to the problem of transient interference suppression. Transients typically consist of an initial peak followed by decaying short-duration oscillations. Such sounds, e.g., keyboard typing and door knocking, often arise as an interference in everyday applications: hearing aids, hands-free accessories, mobile phones, and conference-room devices. We describe a graph construction using a noisy speech signal and training recordings of typical transients. The main idea is to capture the transient interference structure, which may emerge from the construction of the graph. The graph parametrization is then viewed as a data-driven model of the transients and utilized to define a filter that extracts the transients from noisy speech measurements. Unlike previous transient interference suppression studies, in this work the graph is constructed in advance from training recordings. Then, the graph is extended to newly acquired measurements, providing a sequential filtering framework of noisy speech.
|Number of pages||11|
|Journal||IEEE Transactions on Audio, Speech and Language Processing|
|State||Published - 2012|
Bibliographical noteFunding Information:
Manuscript received January 09, 2012; revised April 21, 2012; accepted May 31, 2012. Date of publication June 19, 2012; date of current version August 24, 2012. The work of R. Talmon and I. Cohen work was supported by the Israel Science Foundation under Grant 1130/11. The work of R. Talmon was supported in part by the Viterbi Fellowship, Technion. The work of R. Coifman work was supported by DARPA and the SPAWAR System Center Pacific under Contract N66001-11-C-4092. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Emmanuel Vincent.
- Acoustic noise
- graph filtering
- speech enhancement
- speech processing
- transient noise