Kenzo Itoh

Pure delay effects on speech quality in telecommunications

The effect of transmission delay on speech quality in telecommunications is described, with human factors such as conversational mode and the talkers knowledge of the cause of delay taken into account. Objective quality estimation methods for delay effects are proposed, and these methods are applied in an actual communications network. In connection with delay perception in a telephone conversation, the assumption was verified that a talker expects a particular response time from a partner, and that delay that is outside this expectation time window is noticed. Taking this information into account, a subjective conversational experiment is controlled by six kinds of tasks by varying the temporal characteristics. Thus, a subjective assessment of delay effects is obtained by laboratory tests in relation to the detectability threshold, opinion rating, and conversational efficiency. Objective quality measures for each test were defined as a linear combination of temporal parameters that correspond closely to subjective qualities. >

Objective quality evaluation for low-bit-rate speech coding systems

An LPC (linear predictive coding) cepstrum distance measure (CD) is introduced as an objective measure for estimating the subjective quality of speech signals. Good correspondence between LPC CD and the subjective quality, expressed in terms of both opinion equivalent Q and mean opinion score, are shown. Good repeatability of objective quality evaluation using LPC CD is also shown. A method for generating an artificial voice signal that reflects the characteristics of real speech signals is described. The LPC CD values calculated using this artificial voice are almost the same as those calculated using real speech signals. The speaker-dependency of the coded-speech quality is shown to be an important factor in low-bit-rate speech coding. Even taking this factor into consideration, LPC CD is shown to be effective for estimating the subjective quality. >

Environmental noise reduction based on speech/non-speech identification for hearing aids

We proposed a very practical and useful noise reduction system that has wide application for hearing impaired persons, such as a sound-gathering system at a lecture hall or conference room. The system uses two basic technologies, a speech/non-speech identification process and a new noise reduction process. A speech/non-speech identification process uses four characteristics of the time and frequency domains of the input signal. In the noise reduction process, frequency weighting function is used for basic spectral subtraction and a loss control algorithm. Various kinds of environmental noise were reduced by this system, which showed excellent performance. Noise is further reduced by using a multi-microphone system as an acoustic noise suppressor. The results of intelligibility tests using persons with hearing loss show excellent noise reduction.

Comparison of objective speech quality measures for voiceband CODECs

This paper describes objective quality measures to evaluate speech quality for various kinds of voiceband CODECs in common. The voiceband CODECs studied were PCM, ADM, ADPCM, ATC (Adaptive Transform Coding) and APC-AB (Adaptive Predictive Coding with Adaptive Bit Allocation). First, several objective quality measures in time and frequency domain were defined. They were SNR, Segmental SNR, Spectral Distortion, LPC Cepstrum Distance, COSH, Likelihood Ratio and Weighted Likelihood Ratio. Second, speech quality for voiceband CODECs were evaluated by subjective and objective quality measures. The subjective measures used were based on opinion test and articulation test. Finally, the relationship between objective measures and subjectively evaluated values was studied. It was concluded that the LPC Cepstrum Distance measure had best correspondence to Mean Opinion Score, among the objective measures studied. It was also concluded that the Wighted Likelihood Ratio measure had best correspondence to Articulation Score.

A new waveform speech synthesis approach based on the COC speech spectrum

This paper proposes a high quality speech synthesis system based on waveform synthesis. Our most recent text-to-speech (TTS) system achieved very good performance by using waveform synthesis units. The system, however, required a very large speech data base. A compact system could only be created by developing a very small data package. This paper proposes new approach to speech synthesis based on waveform segments. A novel point of the approach is its simple algorithm which effectively forms synthesis unit package using the clustering technique. The algorithm is applied to our TTS system. Evaluation by listening tests confirm the good performance of the algorithm.<<ETX>>

A new artificial speech signal for objective quality evaluation of speech coding systems

Describes a new artificial speech signal (ASVQ: artificial speech by vector quantization technique) which reflects the average characteristics of the human voice. The ASVQ is intended for use as a test signal in the objective evaluation of speech coding system quality. To obtain the average characteristics, a very large speech data base is analysed, The ASVQ generation method which reflects the extracted average characteristics of the human voice is formulated. This method applies vector quantizing analysis to the speech data base. The LPC speech synthesis circuit is used to reproduce the average characteristics. Finally, the new artificial speech signal is compared with a human voice and the estimation accuracy of the subjective quality of speech coding systems and nonlinear distortions is evaluated. >

Artificial voice signal for objective quality evaluation of speech coding systems

An artificial voice signal that reflects the average characteristics of the human voice is described. This signal is intended for use as a test signal in the objective evaluation of speech coding system quality. To obtain the average characteristics, a multilingual set of speech samples is analyzed. An artificial voice generation method that reflects the extracted average characteristics of a human voice is formulated. This method applies vector quantizing analysis to the multilingual speech database. The partial correlation (PARCOR) speech synthesis circuit is used to reproduce the average characteristics. Finally, the artificial voice is compared with a human voice, and the estimation accuracy of the subjective quality of speech coding systems is evaluated.<<ETX>>