Abstract. The Bonn Open Synthesis System (BOSS) is an open-source software for the unit selection speech synthesis that has been used for the generation of high-quality German and Dutch speech. This article presents ongoing research and development aimed at adapting BOSS to the Polish language. In the first section, the origins and workings of the unit selection method for speech synthesis are explained. Section two details the structure of the Polish corpus and its segmental and prosodic annotation. The subsequent sections focus on the implementation of Polish TTS modules in the BOSS architecture (duration prediction and cost function) and the steps involved in preparing a new speech corpus for BOSS.
The study of speech timing, i.e. the duration and speed or tempo of speech events, has increased in importance over the past twenty years, in particular in connection with increased demands for accuracy, intelligibility and naturalness in speech technology, with applications in language teaching and testing, and with the study of speech timing patterns in language typology. H owever, the methods used in such studies are very diverse, and so far there is no accessible overview of these methods. Since the field is too broad for us to provide an exhaustive account, we have made two choices: first, to provide a framework of paradigmatic (classificatory), syntagmatic (compositional) and functional (discourse-oriented) dimensions for duration analysis; and second, to provide worked examples of a selection of methods associated primarily with these three dimensions. Some of the methods which are covered are established state-of-the-art approaches (e.g. the paradigmatic Classification and Regression Trees, CART , analysis), others are discussed in a critical light (e.g. so-called ‘rhythm metrics’). A set of syntagmatic approaches applies to the tokenisation and tree parsing of duration hierarchies, based on speech annotations, and a functional approach describes duration distributions with sociolinguistic variables. Several of the methods are supported by a new web-based software tool for analysing annotated speech data, the Time Group Analyser.
Emotion lexicons are useful in research across various disciplines, but the availability of such resources remains limited for most languages. While existing emotion lexicons typically comprise words, it is a particular meaning of a word (rather than the word itself) that conveys emotion. To mitigate this issue, we present the Emotion Meanings dataset, a novel dataset of 6000 Polish word meanings. The word meanings are derived from the Polish wordnet (plWordNet), a large semantic network interlinking words by means of lexical and conceptual relations. The word meanings were manually rated for valence and arousal, along with a variety of basic emotion categories (anger, disgust, fear, sadness, anticipation, happiness, surprise, and trust). The annotations were found to be highly reliable, as demonstrated by the similarity between data collected in two independent samples: unsupervised (n = 21,317) and supervised (n = 561). Although we found the annotations to be relatively stable for female, male, younger, and older participants, we share both summary data and individual data to enable emotion research on different demographically specific subgroups. The word meanings are further accompanied by the relevant metadata, derived from open-source linguistic resources. Direct mapping to Princeton WordNet makes the dataset suitable for research on multiple languages. Altogether, this dataset provides a versatile resource that can be employed for emotion research in psychology, cognitive science, psycholinguistics, computational linguistics, and natural language processing.
This article presents research and development aimed at creating a Polish speech database for speech synthesis and adapting BOSS (The Bonn Open Synthesis System) to the Polish language. First of all, the linguistic background for the design of Polish spoken resources for unit selection is presented, together with the presentation of the applied transcription and annotation methods. The next section details the assumptions and the structure of the Polish corpus and its segmental and prosodic annotation. Then, the linguistic features used in duration modelling and the selection of adequate speech units of two Polish modules in BOSS are reported: the duration prediction module (the description is accompanied by a concise overview of Polish duration modelling for speech technology purposes) and the cost functions module. Finally, the results of two kinds of perception tests are discussed: the first is a preference test aimed at the evaluation of synthesized speech obtained using three variants of speech signal segmentation (automatic, semi-automatic and manual) and the second is a mean opinion score test carried out to provide a preliminary assessment of the synthesized speech quality attained with the Polish version of the BOSS synthesizer. The closing chapter summarizes future perspectives and challenges for the Polish TTS (text-to-speech) and further developments of BOSS for Polish.
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