Wyniki wyszukiwania dla: speech recognition
-
Marking the Allophones Boundaries Based on the DTW Algorithm
PublikacjaThe paper presents an approach to marking the boundaries of allophones in the speech signal based on the Dynamic Time Warping (DTW) algorithm. Setting and marking of allophones boundaries in continuous speech is a difficult issue due to the mutual influence of adjacent phonemes on each other. It is this neighborhood on the one hand that creates variants of phonemes that is allophones, and on the other hand it affects that the border...
-
The Innovative Faculty for Innovative Technologies
PublikacjaA leaflet describing Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology. Multimedia Systems Department described laboratories and prototypes of: Auditory-visual attention stimulator, Automatic video event detection, Object re-identification application for multi-camera surveillance systems, Object Tracking and Automatic Master-Slave PTZ Camera Positioning System, Passive Acoustic Radar,...
-
Mispronunciation Detection in Non-Native (L2) English with Uncertainty Modeling
PublikacjaA common approach to the automatic detection of mispronunciation in language learning is to recognize the phonemes produced by a student and compare it to the expected pronunciation of a native speaker. This approach makes two simplifying assumptions: a) phonemes can be recognized from speech with high accuracy, b) there is a single correct way for a sentence to be pronounced. These assumptions do not always hold, which can result...
-
Selection of Features for Multimodal Vocalic Segments Classification
PublikacjaEnglish speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...
-
Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublikacjaIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
-
Biometria i przetwarzanie mowy 2023
Kursy Online{mlang pl} Celem kursu jest zapoznanie studentów z: metodami ustalania i potwierdzania tożsamości ludzi na podstawie mierzalnych cech organizmu cechami mowy ludzkiej, w szczególności polskiej metodami rozpoznawania mowy metodami syntezy mowy {mlang} {mlang en} The aim of the course is to familiarize the students with: methods of identification and verification of identity of people based on measurable features of their...
-
Biometria i przetwarzanie mowy 2024
Kursy Online{mlang pl} Celem kursu jest zapoznanie studentów z: metodami ustalania i potwierdzania tożsamości ludzi na podstawie mierzalnych cech organizmu cechami mowy ludzkiej, w szczególności polskiej metodami rozpoznawania mowy metodami syntezy mowy {mlang} {mlang en} The aim of the course is to familiarize the students with: methods of identification and verification of identity of people based on measurable features of their...
-
Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training
PublikacjaIn the paper we tackle bi-objective execution time and power consumption optimization problem concerning execution of parallel applications. We propose using a discrete-event simulation environment for exploring this power/time trade-off in the form of a Pareto front. The solution is verified by a case study based on a real deep neural network training application for automatic speech recognition. A simulation lasting over 2 hours...
-
Deep neural networks for data analysis
Kursy OnlineThe aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...
-
Orken Mamyrbayev Professor
Osoby1. Education: Higher. In 2001, graduated from the Abay Almaty State University (now Abay Kazakh National Pedagogical University), in the specialty: Computer science and computerization manager. 2. Academic degree: Ph.D. in the specialty "6D070300-Information systems". The dissertation was defended in 2014 on the topic: "Kazakh soileulerin tanudyn kupmodaldy zhuyesin kuru". Under my supervision, 16 masters, 1 dissertation...
-
Performance Analysis of the OpenCL Environment on Mobile Platforms
PublikacjaToday’s smartphones have more and more features that so far were only assigned to personal computers. Every year these devices are composed of better and more efficient components. Everything indicates that modern smartphones are replacing ordinary computers in various activities. High computing power is required for tasks such as image processing, speech recognition and object detection. This paper analyses the performance of...
-
Separability Assessment of Selected Types of Vehicle-Associated Noise
PublikacjaMusic Information Retrieval (MIR) area as well as development of speech and environmental information recognition techniques brought various tools in-tended for recognizing low-level features of acoustic signals based on a set of calculated parameters. In this study, the MIRtoolbox MATLAB tool, designed for music parameter extraction, is used to obtain a vector of parameters to check whether they are suitable for separation of...
-
Towards More Realistic Probabilistic Models for Data Structures: The External Path Length in Tries under the Markov Model
PublikacjaTries are among the most versatile and widely used data structures on words. They are pertinent to the (internal) structure of (stored) words and several splitting procedures used in diverse contexts ranging from document taxonomy to IP addresses lookup, from data compression (i.e., Lempel- Ziv'77 scheme) to dynamic hashing, from partial-match queries to speech recognition, from leader election algorithms to distributed hashing...
-
MODALITY corpus - SPEAKER 35 - COMMANDS C1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 21 - SEQUENCE S6
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 21 - COMMANDS C5
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 21 - SEQUENCE S4
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 10 - SEQUENCE S1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 01 - SEQUENCE S2
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 39 - COMMANDS C1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 01 - SEQUENCE S3
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 01 - COMMANDS C3
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 21 - SEQUENCE S2
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 33 - SEQUENCE S1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 01 - COMMANDS C2
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 21 - COMMANDS C3
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 01 - SEQUENCE S4
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 01 - SEQUENCE S6
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 21 - SEQUENCE S5
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 01 - COMMANDS C4
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 21 - COMMANDS C4
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 01 - COMMANDS C5
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 21 - SEQUENCE S3
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 01 - COMMANDS C6
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 21 - COMMANDS C6
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 35 - SEQUENCE S1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 39 - SEQUENCE S1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 33 - COMMANDS C1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 17 - COMMANDS C1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 21 - COMMANDS C2
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 01 - SEQUENCE S5
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
MODALITY corpus - SPEAKER 17 - SEQUENCE S1
Dane BadawczeThe MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system,...
-
Visual perception of vowels from static and dynamic cues
PublikacjaThe 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,...
-
Detecting Lombard Speech Using Deep Learning Approach
PublikacjaRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
-
Difference in Perceived Speech Signal Quality Assessment Among Monolingual and Bilingual Teenage Students
PublikacjaThe user perceived quality is a mixture of factors, including the background of an individual. The process of auditory perception is discussed in a wide variety of fields, ranging from engineering to medicine. Many studies examine the difference between musicians and non-musicians. Since musical training develops musical hearing and other various auditory capabilities, similar enhancements should be observable in case of bilingual...
-
Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublikacjaThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...