Automatic Parameters Estimation of the D. Klatt Phoneme Duration Model

Kasparaitis, Pijus; Beniušė, Margarita

doi:10.15388/informatica.2016.100

Cited by 3 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The conclusions briefly discuss the possibilities of using this method for the Lithuanian language. Comparable results of Lithuanian phoneme duration models were obtained by Kasparaitis and Beniušė (2016). For duration modelling, the rule-based model proposed by Klatt (1979) was used.…”

Section: Sentence-level Intonation Modellingmentioning

confidence: 99%

An Overview of Lithuanian Intonation: A Linguistic and Modelling Perspective

Melnik-Leroy¹,

Bernatavičienė²,

Korvel³

et al. 2022

Informatica

View full text Add to dashboard Cite

Intonation is a complex suprasegmental phenomenon essential for speech processing. However, it is still largely understudied, especially in the case of under-resourced languages, such as Lithuanian. The current paper focuses on intonation in Lithuanian, a Baltic pitch-accent language with free stress and tonal variations on accented heavy syllables. Due to historical circumstances, the description and analysis of Lithuanian intonation were carried out within different theoretical frameworks and in several languages, which makes them hardly accessible to the international research community. This paper is the first attempt to gather research on Lithuanian intonation from both the Lithuanian and the Western traditions, the structuralist and generativist points of view, and the linguistic and modelling perspectives. The paper identifies issues in existing research that require special attention and proposes directions for future investigations both in linguistics and modelling.

show abstract

Section: Sentence-level Intonation Modellingmentioning

confidence: 99%

An Overview of Lithuanian Intonation: A Linguistic and Modelling Perspective

Melnik-Leroy¹,

Bernatavičienė²,

Korvel³

et al. 2022

Informatica

View full text Add to dashboard Cite

show abstract

“…Many of them are presented as solutions to the 'copy synthesis' problem, which is the problem to estimate the input parameters to reconstruct a speech signal using a speech synthesizer Copy synthesis is a difficult inverse problem because the mapping is non-linear and often is a 'from many to one' problem. One of them is that proposed by Kasparaitis [75], who proposed an iterative algorithm for the automatic estimation of the factors for the Klatt model using the corpus of an annotated audio record of the speaker. Another is that proposed by Laprie, [76], who describe an approach to track formant trajectories first, and to compute the amplitudes of the resonators by an algorithm derived from cepstral smoothing they called "true envelope".…”

Section: Experiments 4: Some Examples Produced For the Italian Languagementioning

confidence: 99%

An Effective and Efficient Genetic-Fuzzy Algorithm for Supporting Advanced Human-Machine Interfaces in Big Data Settings

2019

View full text Add to dashboard Cite

In this paper we describe a novel algorithm, inspired by the mirror neuron discovery, to support automatic learning oriented to advanced man-machine interfaces. The algorithm introduces several points of innovation, based on complex metrics of similarity that involve different characteristics of the entire learning process. In more detail, the proposed approach deals with an humanoid robot algorithm suited for automatic vocalization acquisition from a human tutor. The learned vocalization can be used to multi-modal reproduction of speech, as the articulatory and acoustic parameters that compose the vocalization database can be used to synthesize unrestricted speech utterances and reproduce the articulatory and facial movements of the humanoid talking face automatically synchronized. The algorithm uses fuzzy articulatory rules, which describe transitions between phonemes derived from the International Phonetic Alphabet (IPA), to allow simpler adaptation to different languages, and genetic optimization of the membership degrees. Large experimental evaluation and analysis of the proposed algorithm on synthetic and real data sets confirms the benefits of our proposal. Indeed, experimental results show that the vocalization acquired respects the basic phonetic rules of Italian languages and that subjective results show the effectiveness of multi-modal speech production with automatic synchronization between facial movements and speech emissions. The algorithm has been applied to a virtual speaking face but it may also be used in mechanical vocalization systems as well.

show abstract

“…Despite the fact that duration models of Lithuanian sounds (Norkevičius and Raškinis, 2008), (Kasparaitis and Beniušė, 2016) and the intonation model of Lithuanian sentences (Vaičiūnas et al, 2016) have been developed in recent years, they will not be used in this work because only the phoneme-based synthesizer has the duration model implemented at the moment. Phonemes and diphones will be cut out of the recordings without any modifications.…”

Section: The Problem Of Missing Diphonesmentioning

confidence: 99%

Phoneme vs. Diphone in Unit Selection TTS of Lithuanian

Kasparaitis¹,

Kancys²

2018

BJMC

Self Cite

View full text Add to dashboard Cite

Abstract. The present paper deals with choosing the base type for the unit selection speech synthesis method of the Lithuanian language. Phoneme and diphone units have been examined. Besides, two different methods of joining costs calculation were employed in a diphone synthesizer: one was based on the spectral similarity and the other was based on phonological classes of the sounds to be joined. Synthesizers were evaluated according to their performance, algorithm complexity, the number of joins in a synthesized speech and the human listeners' subjective judgment. Experimental testing showed that the diphone synthesizer based on phonological classes was much more acceptable to the listeners than the one based on the spectral similarity. The diphone synthesizer based on phonological classes outperformed the phonemic synthesizer in terms of performance and the number of joins though it was somewhat less acceptable to human listeners.

show abstract

Automatic Parameters Estimation of the D. Klatt Phoneme Duration Model

Cited by 3 publications

References 5 publications

An Overview of Lithuanian Intonation: A Linguistic and Modelling Perspective

An Overview of Lithuanian Intonation: A Linguistic and Modelling Perspective

An Effective and Efficient Genetic-Fuzzy Algorithm for Supporting Advanced Human-Machine Interfaces in Big Data Settings

Phoneme vs. Diphone in Unit Selection TTS of Lithuanian

Contact Info

Product

Resources

About