Title :
Fixed-Point Implementation of Noise Reduction Using StarCore- SC3400
Author :
Dyba, Roman A. ; Su, Wen Wu ; Deng, Hongyang
Author_Institution :
DSP Voice Enhancement, Network & Multimedia Group, Freescale Semicond., Inc., Austin, TX
Abstract :
The presence of relatively high-level background noise in a telecommunication channel may lower the perceived voice quality of speech signals as well as degrade in-band signaling. The challenge is to reduce the noise to a satisfactory level while minimizing the use of computational resources. This paper describes an efficient noise reduction algorithm and its implementation on a high-performance digital signal processor (DSP) based on the freescale StarCoretrade SC3400 core. The NR implementation methodology takes advantage of the StarCoretrade architecture and Code Warriortrade development tools to reduce engineering efforts. After performing code optimization by exploring a mix of high-level and machine-level languages, the NR computational cost is reduced to approximately 0.6 millions of cycles per second for the narrow-band applications (i.e., G.711 with 8 kHz sampling rate). The algorithm has been evaluated using different approaches, including subjective evaluation by expert listeners. An overall noise reduction of 10-12 dB (for standard setting of 13 dB noise reduction threshold) has been achieved for most natural-speech signals polluted with stationary noise. The noise reduction component has also been evaluated using wideband signals (16 kHz sampling rate). The machine cycle count increased to 1 MCSP (approximately) while the overall noise reduction of 9-12 dB was achieved without observing adverse side effects related to voice quality.
Keywords :
audio signal processing; digital signal processing chips; interference suppression; speech processing; Code Warrior development tools; StarCore architecture; code optimization; computational resources; digital signal processor; fixed-point implementation; freescale StarCore SC3400 core; high level languages; in-band signaling; machine cycle count; machine level languages; natural speech signal; noise reduction algorithm; noise reduction component; noise reduction threshold; stationary noise; telecommunication channel; voice quality; wideband signal; Background noise; Communication channels; Degradation; Digital signal processors; Noise level; Noise reduction; Sampling methods; Signal processing algorithms; Speech enhancement; Telecommunication computing; DSP; Noise Reduction/Supression; Spectral Subtraction;
Conference_Titel :
Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009. DSP/SPE 2009. IEEE 13th
Conference_Location :
Marco Island, FL
Print_ISBN :
978-1-4244-3677-4
Electronic_ISBN :
978-1-4244-3677-4
DOI :
10.1109/DSP.2009.4785920