The paper presents a new corpus of dialogue speech designed specifically for research in the field of speech entrainment. Given that the degree of accommodation may depend on a number of social factors, the corpus is designed to encompass 5 types of relations between the interlocutors: those between siblings, close friends, strangers of the same gender, strangers of the other gender, strangers of which one has a higher job position and greater age. Another critical decision taken in this corpus is that in all these social settings one speaker is kept the same. This allows us to trace the changes in his/her speech depending on the interlocutor. The basic set of speakers consists of 10 pairs of same-gender siblings (including 4 pairs of identical twins) aged 23-40, and each of them was recorded in the 5 settings mentioned above. In total we obtained 90 dialogues of 25-60 minutes each. The speakers played a card game and a map game; they were recorded in a soundproof studio without being able to see each other due to a non-transparent screen between them. The corpus contains orthographic, phonetic and prosodic annotation and is segmented into turns and inter-pausal units.

The current study focuses on optimization of Levenshtein algorithm for the purpose of computing the optimal alignment between two phoneme transcriptions of spoken utterance containing sequences of phonetic symbols. The alignment is computed with the help of a confusion matrix in which costs for phonetic symbol deletion, insertion and substitution are defined taking into account various phonological processes that occur in fluent speech, such as anticipatory assimilation, phone elision and epenthesis. The corpus containing about 30 hours of Russian read speech was used to evaluate the presented algorithms. The experimental results have shown significant reduction of misalignment rate in comparison with the baseline Levenshtein algorithm: the number of errors has been reduced from 1.1 % to 0.28 %

This paper describes speech data recording, processing and annotation of a new speech corpus CoRuSS (Corpus of Russian Spontaneous Speech), which is based on connected communicative speech recorded from 60 native Russian male and female speakers of different age groups (from 16 to 77). Some Russian speech corpora available at the moment contain plain orthographic texts and provide some kind of limited annotation, but there are no corpora providing detailed prosodic annotation of spontaneous conversational speech. This corpus contains 30 hours of high quality recorded spontaneous Russian speech, half of it has been transcribed and prosodically labeled. The recordings consist of dialogues between two speakers, monologues (speakers’ self-presentations) and reading of a short phonetically balanced text. Since the corpus is labeled for a wide range of linguistic - phonetic and prosodic - information, it provides basis for empirical studies of various spontaneous speech phenomena as well as for comparison with those we observe in prepared read speech. Since the corpus is designed as a open-access resource of speech data, it will also make possible to advance corpus-based analysis of spontaneous speech data across languages and speech technology development as well.

The paper introduces CORPRES ― a fully annotated Russian speech corpus developed at the Department of Phonetics, St. Petersburg State University as a result of a three-year project. The corpus includes samples of different speaking styles produced by 4 male and 4 female speakers. Six levels of annotation cover all phonetic and prosodic information about the recorded speech data, including labels for pitch marks, phonetic events, narrow and wide phonetic transcription, orthographic and prosodic transcription. Precise phonetic transcription of the data provides an especially valuable resource for both research and development purposes. Overall corpus size is 528 458 running words and contains 60 hours of speech made up of 7.5 hours from each speaker. 40% of the corpus was manually segmented and fully annotated on all six levels. 60% of the corpus was partly annotated; there are labels for pitch period and phonetic event labels. Orthographic, prosodic and ideal phonetic transcription for this part was generated and stored as text files. The fully annotated part of the corpus covers all speaking styles included in the corpus and all speakers. The paper contains information about CORPRES design and annotation principles, overall data description and some speculation about possible use of the corpus.