When a disaster strikes, many people make calls to their loved ones in the affected area. As a result, telephone networks become congested, making it difficult for people to contact each other. This congestion continues in the aftermath of a large-scale disaster. The sooner the congestion is eased, the sooner and easier people can contact each other. We accomplish this by reducing communication demand without directly restricting call duration. We propose a congestion control method, called the road space rationing (RSR) method (RSR was originally designed for transportation and restricts access to congested areas on the basis of the last digit of a vehicle’s license plate or license number). Our RSR method only restricts the period in which to make a call on the basis of the last digits of calling parties’ phone numbers (e.g., only people with phone numbers ending in 1 can make calls between XX:06 and XX:12). It not only avoids restricting the overall number of calling parties but also prompts people to reduce their call duration consciously despite it being unrestricted. It thus has a mechanism to change human communication behavior without directly restricting call duration. This consciously willed reduction is effective against disaster congestion because there are no redials to the same called parties. This reduction in call duration in turn decreases congestion. Experimental results revealed that the RSR method reduced call duration by 30%.

This paper presents a real-time robust formant tracking system for speech signals and electroglottography (EGG) signals using a real-time phase equalization-based autoregressive exogenous model (RT-PEAR). PEAR can estimate formant frequencies robustly even for speech with high fundamental frequencies using phase equalization preprocessing and LPC with an impulse train. To reduce the computational complexity of original PEAR, a novel formulation of LPC with an impulse train is derived. EGG signals were used for stable detection of pitch marks since PEAR requires them. Formant estimation errors for the proposed method were less than 5 % regardless of fundamental frequencies with 12-ms processing delay. This technique will be useful for real-time speech conversion and speech-language therapy.

This paper presents a novel method for estimating a vocal-tract spectrum from speech signals, based on a modeling of excita-tion signals of voiced speech. A formulation of linear prediction coding with impulse train is derived and applied to the phase-equalized speech signals, which are converted from the original speech signals by phase equalization. Preliminary results show that the proposed method improves the robustness of the estima-tion of a vocal-tract spectrum and the quality of re-synthesized speech compared with the conventional method. This technique will be useful for speech coding, speech synthesis, and real-time speech conversion. Index Terms: LPC, vocal-tract spectrum, phase equalization 1.

We present a multi-speaker articulatory reconstruction method based on speaker-independent articulatory features and speaker-dependent features. These features are separated by using a multi-speaker articulatory database. This separation method consists of normalizing palate positions among the speakers and separating multi-speaker articulatory data into a speaker-independent eigen articulatory HMM and a speaker-adaptive matrix by using speaker-adaptive training (SAT). With the proposed method, the average RMS errors of the measured and reconstructed articulatory parameters were 1.35 mm. This result shows that the proposed method makes it possible to control speaker idiosyncrasies in the articulatory parameter domain.

This paper describes development of a new human-like talking robot WT-4 (Waseda Talker No. 4). WT-4 was developed to overcome the problems related to the lack of variation in the formant frequency of the sounds generated by the previous talking robot WT-3. These problems arose particularly on the first formant (F1) where frequencies of less than 500 [Hz] could not be reached. And the differences among WT-3’s vowels were not clear; which may have been caused by the sound source of the vocal cords and the lips. Therefore, the connection between the vocal cords and the vocal tract was improved, as well as the lips mechanism. As the result of these improvements, WT-4’s sounds were quite similar to a human’s, and WT-4 was able to reproduce suitable sounds using auditory feedback.

This paper describes the mechanisms and the speech production of a new advanced talking robot WT-3 (Waseda Talker-No.3) that improves on WT-2 (Waseda Talker-No.2) and is based on human acoustic theory for the reproduction of human speech. WT-3 consists of 1-DOF lungs and 3-DOF vocal cords and articulators (the 7-DOF tongue, 5-DOF lips, 1-DOF teeth, nasal cavity and 1-DOF soft palate), and can reproduce human-like articulatory motion; the total DOF is 18. The oral cavity is designed based on the MRI images of the human sagittal plane, although the cross section of the vocal tract is rectangular in shape except for the mouth. The width of the vocal tract is 30 [mm]. The average length of the vocal tract is approximately 175 [mm] and the same as that of a human's. Compared to the previous robots, WT-3 can produce vowels more clearly, and produce stops, fricatives and nasal sounds with the new flexible mechanisms that function as the human vocal tract area and the other mechanisms. WT-3 can mechanically reproduce human speech.

This paper describes an autonomous control method of an anthropomorphic talking robot WT-4 (Waseda Talker No.4) to mimic continuous human speech sounds by auditory feedback. WT-4 consisted of 1-DOF lungs, 4-DOF vocal cords and articulators (the 7-DOF tongue, 5-DOF lips, 1-DOF teeth, nasal cavity and 1-DOF soft palate), and could reproduce human-like articulatory motion; the total DOF was 19. In this method, the trajectory of each robot parameter was controlled so that the acoustic parameters (pitch, sound power, formant frequencies that are resonant frequencies of the vocal tract and have the peak of the output spectrum, and the timing of the switch between voiced and voiceless sounds) generated from the robot were close to those of human speech sounds. The trajectory of each robot parameter was optimized by inputting the acoustic parameters. This method would help to clarify the human speech mechanism and to create a new speech production system.

This paper describes the development of a new talking robot WT-2 that improved on WT-1R and has advanced vocal tract mechanisms for the reproduction of human vocal movement. WT-2 consists lungs, vocal cords, a vocal cavity and nasal cavity; the total DOF is 15. The length of the vocal tract is about 175 mm and is almost the same as that of an adult male. Compared to WT-1 or WT-1R developed previously, WT-2 could utter Japanese vowels more clearly, and produce stops, fricatives and nasal sounds by a new flexible tongue mechanism as well as decrease sound leaks from the tongue except those from the lips or nostrils.

This paper describes the modeling and analysis of an elastic tongue mechanism of a talking robot WT-2 and the development of an acoustic simulator for the construction of the computational model of human speech production. WT-2 consists of lungs, vocal cords and articulators. It is essential to accurately estimate and analyze the shapes of these organs to develop an acoustic simulator. However, it was difficult to estimate and analyze the mechanisms, because they were composed of an elastic rubber to make various shapes and to seal the air and sound. Therefore, we constructed a modeling method to simulate the shape of the elastic mechanisms. This method is applicable to all the elastic body. We developed an acoustic simulator using this modeling method in the process of constructing the speech production model.

This paper describes the speech planning of the anthropomorphic talking robot WT-1R (Waseda Talker-No.1 Refined) for the production of consonant sounds. WT-1R has articulators (the tongue, lips, teeth, nasal cavity and soft palate) and vocal organs (the lungs and vocal cords), and can reproduce human vocal movement. Its total DOF (degrees of freedom) is 15. The vocal movement of WT-1R for vowels is steady. We produced Japanese vowels (/a/, /i/, /u/, /e/, /o/) using the first robot WT-1 in 2000. However, the vocal movement for consonant sounds is transient. We must control the 15-DOF talking robot coordinately in the space and time to reproduce the complicated phenomena of the consonant sounds. Therefore, because the Japanese voice generally consists of two phonemes of the first consonant sound and the last vowel, we proposed the speech planning of WT-1R by considering the phenomenon of the voice as three parts (steady consonant sound, transient consonant sound and vowel). WT-1R could produce Japanese vowels (/a/, /i/, /u/, /e/, /o/) and some consonant sounds (/s/, /h/, /m/, /p/ and /waseda/).

This research attempts to clarify the human vocal mechanism from engineering viewpoints by simulating the vocal movement with a robot, and to create a dynamic model. The authors developed an anthropomorphic talking robot, WT-1 (Waseda Talker-No.1) in 1999. It simulated the human vocal movement,. and had articulators and vocal organs. WT-1 could speak Japanese vowels (|a|, |i|, |u|, |e|, |o|). However, the vowels produced were not natural. Therefore, we develop a refined talking robot WT-1R that improves the realization of natural vowels and consonant sounds. WT-IR has articulators (the 6-DOF tongue, 4-DOF lips, 1-DOF teeth, a nasal cavity and a 1-DOF soft palate) and vocal organs (the 1-DOF lungs, 2-DOF vocal cords). The total DOF of the robot is 15. This paper describes the improved mechanisms of WT-IR and the realization of the fluctuation for the natural voice and the clearness of vowels.