Phonetic transcription of text is an indispensable component of text-to-speech (TTS) systems and is used in acoustic modeling for speech recognition and other natural language processing applications. One approach to the transcription of written text into phonetic entities or sounds is to use a set of well-defined context and language-dependent rules. The process of transcribing text into sounds starts by preprocessing the text and representing it by lexical items to which the rules are applicable. The rules can be segregated into phonemic and phonetic rules. Phonemic rules operate on graphemes to convert them into phonemes. Phonetic rules operate on phonemes and convert them into context-dependent phonetic entities with actual sounds. Converting from written text into actual sounds, developing a comprehensive set of rules, and transforming the rules into implementable algorithms for any language cause several problems that have their origins in the relative lack of correspondence between the spelling of the lexical items and their sound contents. For Standard Malay (SM) these problems are not as severe as those for languages of complex spelling systems, such as English and French, but they do exist. In this paper, developing a comprehensive computerized system for processing SM text and transcribing it into phonetic entities and evaluating the performance of this system, irrespective of the application, is discussed. In particular, the following issues are dealt with in this paper: (1) the spelling and other problems of SM writing and their impact on converting graphemes into phonemes, (2) the development of a comprehensive set of grapheme-to-phoneme rules for SM, (3) a description of the phonetic variations of SM or how the phonemes of SM vary in context and the development of a set of phoneme-to-phonetic transcription rules, (4) the formulation of the phonemic and phonetic rules into algorithms that are applicable to the computer-based processing of input SM text, and (5) the evaluation of the performance of the process of converting SM text into actual sounds by the above mentioned methods.

Accurate estimation of accentual attribute values of words, which is required to apply rules of Japanese word accent sandhi to prosody generation, is an important factor to realize high-quality text-to-speech (TTS) conversion. The rules were already formulated by Sagisaka et al. and are widely used in Japanese TTS conversion systems. Application of these rules, however, requires values of a few accentual attributes of each constituent word of input text. The attribute values cannot be found in any public database or any accent dictionaries of Japanese. Further, these values are difficult even for native speakers of Japanese to estimate only with their introspective consideration of properties of their mother tongue. In this paper, an algorithm was proposed, where these values were automatically estimated from a large amount of data of accent types of accentual phrases, which were collected through a long series of listening experiments. In the proposed algorithm, inter-speaker differences of knowledge of accent sandhi were well considered. To improve the coverage of the estimated values over the obtained data, the rules were tentatively modified. Evaluation experiments using two-mora accentual phrases showed the high validity of the estimated values and the modified rules and also some defects caused by varieties of linguistic expressions of Japanese.

The authors developed a portable Japanese text-to-speech system using a pocket-sized formant speech synthesizer. It consists of a linguistic processor and an acoustic processor. The linguistic processor runs on an MS-DOS personal computer and has functions to determine readings and prosodic information for input sentences written in kana-kanji-mixed style. New techniques, such as minimization of a cost function for phrases, rare-compound flag, semantic information, information of reading selection and restriction by associated particles, are used to increase the accuracy of readings and accent positions. The accuracy of determining readings and accent positions is 98.6% for sentences in newspaper articles. It is possible to use the linguistic processor through an interface library which has also been developed by the authors. Consequently, it has become possible not only to convert whole texts stored in text files but also to convert parts of sentences sent by the interface library sequentially, and the readings and prosodic information are optimized for the whole sentence at one time. The acoustic processor is custom-made hardware, and it has adopted new techniques, for the improvement of rules for vowel devoicing, control of phoneme durations, control of the phrase components of voice fundamental frequency and the construction of the acoustic parameter database. Due to the above-mentioned modifications, the naturalness of synthetic speech generated by a Klatt-type formant speech synthesizer was improved. On a naturalness test it was rated 3.61 on a scale of 5 points from 0 to 4.

A text-to-speech conversion system for Japanese has been developed for the purpose of producing high-quality speech output. This system consists of four processing stages: 1) linguistic processing, 2) phonological processing, 3) control parameter generation, and 4) speech waveform generation. Although the processing at the first stage is restricted to the texts on general weather conditions, the other three stages can also cope with texts of news and narrations on other topics. Since the prosodic features of speech are largely related to the linguistic information, such as word accent, syntactic structure and discourse structure, linguistic processing of a wider range than ever, at least a sentence, is indispensable to obtain good quality speech with respect to the prosody. From this point of view, input text was restricted to the weather forecast sentences and a method for linguistic processing was developed to conduct morpheme, syntactic and semantic analyses simultaneously. A quantitative model for generating fundamental frequency contours was adopted to make a good reflection of the linguistic information on the prosody of synthetic speech. A set of prosodic rules was constructed to generate prosodic symbols representing prosodic structures of the text from the linguistic information obtained at the first stage. A new speech synthesizer based on the terminal analog method was also developed to improve the segmental quality of synthetic speech. It consists of four paths of cascade connection of pole/zero filters and three waveform generators. The four paths are respectively used for the synthesis of vowels and vowel-like sounds, nasal murmur and buzz bar, friction, and plosion, while the three generators produce voicing source waveform approximated by polynomials, white Gaussian noise source for fricatives and impulse source for plosives. The validity of the approach above has been confirmed by the listening tests using speech synthesized by the developed system. Improvements both in the quality of prosodic features and in the quality of segmental features were realized for the synthetic speech.