Search
Filters
total: 10
Search results for: vowel system
-
Vowel recognition based on acoustic and visual features
PublicationW artykule zaprezentowano metodę, która może ułatwić naukę mowy dla osób z wadami słuchu. Opracowany system rozpoznawania samogłosek wykorzystuje łączną analizę parametrów akustycznych i wizualnych sygnału mowy. Parametry akustyczne bazują na współczynnikach mel-cepstralnych. Do wyznaczenia parametrów wizualnych z kształtu i ruchu ust zastosowano Active Shape Models. Jako klasyfikator użyto sztuczną sieć neuronową. Działanie systemu...
-
Analysis of the harmonic structure of the vowel /a/ taking into account the age and gender of the speaker
PublicationSound waves are disturbances propagating through an elastic medium that, upon reaching the ear, elicit auditory sensations. Sounds generated by the surroundings can be captured by a transducer (microphone), which transforms them into an electrical signal. The signal from the microphone is then transmitted to a computer, where software allows for the extraction and analysis of individual tones. This process enables the description...
-
A system for singing training
PublicationThe system proposed is aimed at the vocal students and persons who want to improve emission of their voices. The goal is not to substituite a singing teacher but to provide a tool for automatic teaching of voice emission basics. In this way singers can develop their vocal skills and improve them. By a visual feedback a student can control and modify vocal tract maximas (resonances) of a chosen vowel to match the resonances of the...
-
Language material for English audiovisual speech recognition system developmen . Materiał językowy do wykorzystania w systemie audiowizualnego rozpoznawania mowy angielskiej
PublicationThe bi-modal speech recognition system requires a 2-sample language input for training and for testing algorithms which precisely depicts natural English speech. For the purposes of the audio-visual recordings, a training data base of 264 sentences (1730 words without repetitions; 5685 sounds) has been created. The language sample reflects vowel and consonant frequencies in natural speech. The recording material reflects both the...
-
"Ash" [æ] sound then and now: an overview of the current state of knowledge
PublicationThe objective of this article is to review the existing studies on the British Received Pronunciation “ash” [æ] sound, as well as its variations outside the United Kingdom. It starts with a short analysis of sociolinguistic aspects of the Received Pronunciation accent, then it points out the most conspicuous differences between the Received Pronunciation and General American vowel systems. Then, it presents the early beginnings...
-
Visual perception of vowels from static and dynamic cues
PublicationThe purpose of the study was to analyse human identification of Polish vowels from static and dynamic durationally slowed visual cues. A total of 152 participants identified 6 Polish vowels produced by 4 speakers from static (still images) and dynamic (videos) cues. The results show that 59% of static vowels and 63% of dynamic vowels were successfully identified. There was a strong confusion between vowels within front, central,...
-
Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling
PublicationPhoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support...
-
Auditory Brainstem Responses recorded employing Audio ABR device
Open Research DataThe dataset consists of ABR measurements employing click, burst and speech stimuli. Parameters of the particular stimuli were as follows:
-
Speech Analytics Based on Machine Learning
PublicationIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
-
MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...