The UPC Text-to-Speech System for Spanish and Catalan

This paper summarizes the text-to-speech system that has been developed in the Speech Group of the Universitat Politècnica de Catalunya (UPC). The system is composed of a core and different interfaces so that it is compatible for research, for telephone applications (either CTI boards or standard ISDN PC cards supporting CAPI), and Windows applications developed using Microsoft SAPI. The paper reviews the system making emphasis in the parts of the system which are language dependent and which allow the reading of bilingual text (Spanish and Catalan). The paper also presents new approaches in prosodic modeling (segmental duration modeling) and generation of the database of speech segments, which have been introduced last year.Peer ReviewedPostprint (published version

Modern speech synthesis for phonetic sciences: a discussion and an evaluation

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A framework to evaluate and verify the presence of linguistic concepts in the prosody of spoken utterances

With recent developments in controlling the prosodic output of speech synthesizers[1], the quality of synthetic speech has improved considerably. However, determining the prosody required to convey specific linguistic concepts is still a largely unsolved problem. Concept-to-speech systems seem the most promising: additional information (structuring, focussing, affirmation/negation, quotation, enumeration, time/date, salutation, speaker attitude, etc.) is available to the prosody generation algorithm. This paper describes a method for determining which linguistic concepts are present in the prosody of a spoken utterance and which should therefore be taken into account when modelling prosody

Concatenative speech synthesis: a Framework for Reducing Perceived Distortion when using the TD-PSOLA Algorithm

This thesis presents the design and evaluation of an approach to concatenative speech synthesis using the Titne-Domain Pitch-Synchronous OverLap-Add (I'D-PSOLA) signal processing algorithm. Concatenative synthesis systems make use of pre-recorded speech segments stored in a speech corpus. At synthesis time, the `best' segments available to synthesise the new utterances are chosen from the corpus using a process known as unit selection. During the synthesis process, the pitch and duration of these segments may be modified to generate the desired prosody. The TD-PSOLA algorithm provides an efficient and essentially successful solution to perform these modifications, although some perceptible distortion, in the form of `buzzyness', may be introduced into the speech signal. Despite the popularity of the TD-PSOLA algorithm, little formal research has been undertaken to address this recognised problem of distortion. The approach in the thesis has been developed towards reducing the perceived distortion that is introduced when TD-PSOLA is applied to speech. To investigate the occurrence of this distortion, a psychoacoustic evaluation of the effect of pitch modification using the TD-PSOLA algorithm is presented. Subjective experiments in the form of a set of listening tests were undertaken using word-level stimuli that had been manipulated using TD-PSOLA. The data collected from these experiments were analysed for patterns of co- occurrence or correlations to investigate where this distortion may occur. From this, parameters were identified which may have contributed to increased distortion. These parameters were concerned with the relationship between the spectral content of individual phonemes, the extent of pitch manipulation, and aspects of the original recordings. Based on these results, a framework was designed for use in conjunction with TD-PSOLA to minimise the possible causes of distortion. The framework consisted of a novel speech corpus design, a signal processing distortion measure, and a selection process for especially problematic phonemes. Rather than phonetically balanced, the corpus is balanced to the needs of the signal processing algorithm, containing more of the adversely affected phonemes. The aim is to reduce the potential extent of pitch modification of such segments, and hence produce synthetic speech with less perceptible distortion. The signal processingdistortion measure was developed to allow the prediction of perceptible distortion in pitch-modified speech. Different weightings were estimated for individual phonemes,trained using the experimental data collected during the listening tests.The potential benefit of such a measure for existing unit selection processes in a corpus-based system using TD-PSOLA is illustrated. Finally, the special-case selection process was developed for highly problematic voiced fricative phonemes to minimise the occurrence of perceived distortion in these segments. The success of the framework, in terms of generating synthetic speech with reduced distortion, was evaluated. A listening test showed that the TD-PSOLA balanced speech corpus may be capable of generating pitch-modified synthetic sentences with significantly less distortion than those generated using a typical phonetically balanced corpus. The voiced fricative selection process was also shown to produce pitch-modified versions of these phonemes with less perceived distortion than a standard selection process. The listening test then indicated that the signal processing distortion measure was able to predict the resulting amount of distortion at the sentence-level after the application of TD-PSOLA, suggesting that it may be beneficial to include such a measure in existing unit selection processes. The framework was found to be capable of producing speech with reduced perceptible distortion in certain situations, although the effects seen at the sentence-level were less than those seen in the previous investigative experiments that made use of word-level stimuli. This suggeststhat the effect of the TD-PSOLA algorithm cannot always be easily anticipated due to the highly dynamic nature of speech, and that the reduction of perceptible distortion in TD-PSOLA-modified speech remains a challenge to the speech community

Turkish text to speech system

Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2002.Thesis (Master's) -- Bilkent University, 2002.Includes bibliographical references leaves 48-51.Scientists have been interested in producing human speech artificially for more than two centuries. After the invention of computers, computers have been used in order to synthesize speech. By the help of this new technology, Text To Speech (TTS) systems that take a text as input and produce speech as output have been created. Some languages like English and French have taken most of the attention and some languages like Turkish have not been taken into consideration. This thesis presents a TTS system for Turkish that uses the diphone concatenation method. It takes a text as input and produces corresponding speech in Turkish. The output can be obtained in one male voice only in this system. Since Turkish is a phonetic language, this system also can be used for other phonetic languages with some minor modifications. If this system is integrated with a pronunciation unit, it can also be used for languages that are not phonetic.Eker, BarışM.S

Text-Independent Voice Conversion

This thesis deals with text-independent solutions for voice conversion. It first introduces the use of vocal tract length normalization (VTLN) for voice conversion. The presented variants of VTLN allow for easily changing speaker characteristics by means of a few trainable parameters. Furthermore, it is shown how VTLN can be expressed in time domain strongly reducing the computational costs while keeping a high speech quality. The second text-independent voice conversion paradigm is residual prediction. In particular, two proposed techniques, residual smoothing and the application of unit selection, result in essential improvement of both speech quality and voice similarity. In order to apply the well-studied linear transformation paradigm to text-independent voice conversion, two text-independent speech alignment techniques are introduced. One is based on automatic segmentation and mapping of artificial phonetic classes and the other is a completely data-driven approach with unit selection. The latter achieves a performance very similar to the conventional text-dependent approach in terms of speech quality and similarity. It is also successfully applied to cross-language voice conversion. The investigations of this thesis are based on several corpora of three different languages, i.e., English, Spanish, and German. Results are also presented from the multilingual voice conversion evaluation in the framework of the international speech-to-speech translation project TC-Star