Real-time Signal Processing Algorithms

Cochlear implant (CI) patients have difficulty
understanding tonal languages which use pitch
variations to convey meaning because of poor pitch
perception. The ability of CI patients to communicate
in noisy environments is severely degraded.
Therefore, pitch-detection and (spatial) noise
suppression is of importance to current cochlear
implant devices. This thesis provides the details of
real-time implementations that address these
concerns. A pitch-detector was implemented to
estimate the pitch and a beamformer was implemented
to suppress spatial noise. The pitch-detection and
the beamforming algorithms were implemented on an ARM
based processor of a Personal Digital Assistant
(PDA). The pitch-detection algorithm is based on the
autocorrelation function. Its real-time performance
was measured and its efficiency in the presence of
speech-shaped noise and babble noise was evaluated.
The beamforming algorithm implemented was the
Griffith s beamformer. Objective and subjective tests
for different signal-to-noise ratio levels of
speech-shaped noise were conducted to evaluate its
performance. This thesis includes the results of
these evaluations.

Autorentext

Rohith Ramachandran was born in Bangalore,India. He entered M. SRamaiah Institute of Technology, Bangalore in October 2000,topursue his Bachelor's degree in Electronics and CommunicationsEngineering. From August 2006, he has been a student in TheUniversity of Texas at Dallas to pursue his Master of Sciencedegree in Electrical Engineering.

Klappentext

Cochlear implant (CI) patients have difficultyunderstanding tonal languages which use pitchvariations to convey meaning because of poor pitchperception. The ability of CI patients to communicatein noisy environments is severely degraded.Therefore, pitch-detection and (spatial) noisesuppression is of importance to current cochlearimplant devices. This thesis provides the details ofreal-time implementations that address theseconcerns. A pitch-detector was implemented toestimate the pitch and a beamformer was implementedto suppress spatial noise. The pitch-detection andthe beamforming algorithms were implemented on an ARMbased processor of a Personal Digital Assistant(PDA). The pitch-detection algorithm is based on theautocorrelation function. Its real-time performancewas measured and its efficiency in the presence ofspeech-shaped noise and babble noise was evaluated.The beamforming algorithm implemented was theGriffith's beamformer. Objective and subjective testsfor different signal-to-noise ratio levels ofspeech-shaped noise were conducted to evaluate itsperformance. This thesis includes the results ofthese evaluations.