Data processing: speech signal processing – linguistics – language – Audio signal bandwidth compression or expansion
Reexamination Certificate
2000-03-23
2003-06-24
Abebe, Daniel (Department: 2654)
Data processing: speech signal processing, linguistics, language
Audio signal bandwidth compression or expansion
C704S222000, C084S600000
Reexamination Certificate
active
06584442
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates generally to methods of compressing waveforms of musical tones, voices and various other sounds by use of a vector quantization technique. More particularly, the present invention relates to an improved waveform compression method which can efficiently compress waveform data, e.g., in a situation where a great number of sets of waveform data are prestored in memory in corresponding relation to a variety of rendition styles (performance styles), as well as to a waveform generation method of using such an improved waveform compression method to generate a desired waveform.
The present invention also relates to a waveform generation method of generating a desired waveform using the improved waveform compression method, which is characterized by improved compression of a non-harmonic (i.e., non-periodic) wave components. The present invention relates further to an improvement method that is directed to generating a desired waveform of a non-periodic wave component.
The principles of present invention described hereinbelow can be applied so extensively to apparatus and methods in all fields which have functions of generating musical tones, voices and other sounds, such as automatic performance apparatus, computers, electronic game apparatus and other multimedia equipment, to say nothing of electronic musical instruments. Note that the terms “tone waveform” are used in this patent specification to refer to not only to a waveform of a musical tone but also a waveform of a voice or any other sound.
In the electronic tone synthesis techniques known today, the issue of how to synthesize high-quality tones taking into consideration (or reflecting) different rendition styles is getting more and more important. Namely, in the field of natural musical instruments, it has been known that even a tone of a same instrument tone color and same pitch is generated with different tonal characteristics (particularly, different tone color waveforms) in response to performance in different rendition styles, such as a vibrato rendition style and slur rendition style. When such high-quality tones reflecting differences in the rendition styles are to be generated by an electronic musical instrument or the like using an electronic tone synthesis technique, one possible approach is to prestore into memory, for each tone pitch (or range) of each instrument tone color, different sets of waveform data presenting tonal characteristics (especially, tone color waveforms) corresponding to the different rendition styles in association with the rendition styles. In this approach, a tone waveform presenting unique tonal characteristics (especially, a unique tone color waveform) corresponding to a selected rendition style can be generated by reading out one of the waveform data sets which corresponds to the selected rendition style.
In the case where different sets of waveform data are prestored, for each tone pitch (or range) of each instrument tone color, in association with a plurality of rendition styles as mentioned above, the necessary memory storage capacity has to be increased considerably if the waveform data are prestored in an ordinary manner. Thus, how to compress the waveform data efficiently and thereby save the memory storage capacity would become an important challenge. For this reason, some of the conventionally-known waveform data compression techniques which are considered most noteworthy in connection with the present invention will be discussed below.
First, Japanese Patent Laid-open Publication No. SHO-61-104400 discloses a sound recording method, in accordance with which an input waveform is separated, via a filtering process, into a periodic wave component and a non-periodic wave component and the thus-separated periodic and non-periodic wave components are encoded by use of different data-compressing coding schemes and then individually stored into a waveform memory. Although this No. HEI-61-104400 publication teaches the idea of separating specific waveform data into periodic and non-periodic wave components and storing them in compressed data formats, it does not teach the idea of vector-quantizing all of the wave components. For the non-periodic wave component, in particular, the disclosed technique can merely record a residual waveform, obtained by subtracting a waveform of the periodic wave component from the specific waveform data, in a time-serial manner just as it is.
Further, in Japanese Patent Laid-open Publication No. HEI-5-88911, there is disclosed a sound coding method using vector quantization. According to the disclosure, a sound waveform to be compressed is first processed by a filter with characteristics opposite to a spectrum extracted from the sound waveform, and then vector quantization is performed on the periodic wave component of the thus-filtered sound waveform using an excitation vector extracted from a predetermined previous cycle of the sound waveform and also-on the non-periodic wave component of the sound waveform using a noise vector. In the disclosed method, the noise vector is one provided in advance merely as a fixed vector, and the non-periodic wave component is not extracted directly from the sound waveform for the vector quantization based on the noise vector.
However, because the data compression rate is relatively low in the first-mentioned waveform data compression technique (Japanese Patent Laid-open Publication No. SHO-61-104400), it is difficult to achieve sufficient data compression that suits the purpose of storing, for each tone pitch (or range) of each instrument tone color, different sets of waveform data in association with a plurality of rendition styles. Namely, because the above-mentioned waveform data compression technique completely lacks the idea of vector-quantizing the non-periodic wave component, it can do nothing, about data storage of the non-periodic wave component, more than just recording the residual waveform (obtained by subtracting the waveform of the periodic wave component from the sound waveform) in a time series just as it is, and therefore the conventional waveform data compression technique never achieves sufficient data compression.
Further, because the second-mentioned waveform data compression technique (Japanese Patent Laid-open Publication No. HEI-5-88911) uses, as the noise vector, one previously provided as a fixed vector and, besides, is not arranged to extract the non-periodic wave component (noise component) directly from the sound waveform for the subsequent vector quantization, the vector quantization using the noise vector would be performed with poor accuracy, and the non-periodic wave component can never be compressed efficiently and also can never be reproduced with good accuracy. Further, because the filtering process is always performed using the opposite characteristics, the waveform to be reproduced would unavoidably assume a shape substantially different from the original waveform shape due to the intervention of the filtering process of the strong opposite characteristics, which would result in even poorer waveform reproducibility. Therefore, this conventional waveform data compression technique can not be used suitably for waveform reproduction of a musical instrument tone of which highly accurate waveform reproducibility is normally required, although it may be suitable for use in waveform reproduction of a human voice of which very accurate waveform reproducibility is not required. Furthermore, in this conventional waveform data compression technique, which performs the waveform compression using both the periodic vector and the noise vector, there would arise a need to perform the vector quantization, based on a combination of the periodic and noise vectors, on a single waveform having undergone the opposite-characteristic filtering process, which thus presents the problems that such a combination of the periodic and noise vectors can not be determined easily and the waveform data can not be compressed with sufficient accuracy. In addition
Sakama Masao
Suzuki Hideo
Abebe Daniel
Morrison & Foerster / LLP
Yamaha Corporation
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