Michael Galler

Enhancement of esophageal speech by injection noise rejection

Esophageal speakers, who produce a voice source by bringing about a vibration of the esophageal superior sphincter, must insufflate the esophagus with an air injection gesture before every utterance, thus creating an air reservoir to drive the vibration. The resulting noise is generally undesired by the speakers. This paper describes a method for the automatic recognition and rejection of the injection noise which occurs in esophageal speech.

Esophageal speech injection noise detection and rejection

The present invention eliminates injection noise in speech produced by esophageal speakers. A speech input signal is digitized. One copy of the digitized signal is used for analysis and the other is passed through a gain switch to an amplifier as output. A Fast Fourier Transform and a mean value of the digitized speech input signal is calculated. The Fast Fourier Transform (FFT) is passed through a morphological filter to produce a filtered spectrum. An occurrence of injection noise is detected by calculating a derivative of the filtered spectrum and determining from the mean value and the derivative a location and value of a largest peak and a second largest peak in the filtered spectrum. If the largest peak is lower in frequency than the second largest peak, and if all points above 2 KHz are less than the mean, then an occurrence of injection noise has been detected. An occurrence of silence is detected by center-clipping the filtered spectrum and determining whether there is any energy within a sliding 10 millisecond window for a predetermined amount of time. If no energy is detected within a sliding 10 millisecond window for a predetermined amount time, then an occurrence of silence has been detected. The output speech signal is passed after the occurrence of injection noise has been detected; and is blocked following an occurrence of silence.

Robustness improvements in continuously spelled names over the telephone

A speaker-independent speech recognizer for continuously spelled names, implemented for a switchboard call-routing task, is analyzed for sources of error. Results indicate most errors are due to extraneous speech and end-point detection errors. Strategies are proposed for improving the robustness of recognition, including tolerance for speech with pauses, and a letter-spotting strategy to handle extraneous speech. Experimental results on laboratory data indicate that with the letter-spotting method, name retrieval error rate is reduced on noisy signals or signals with extraneous speech 60.1%, while it is increased on clean signals from 4.5% to 5.5%. On data collected during a telephone field trial, name retrieval error is reduced 54.1% in offline tests by introducing the letter-spotting algorithm.