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Non-native Speech Database
A non-native speech database is a Speech corpus, speech database of non-native pronunciations of English. Such databases are used in the development of: multilingual automatic speech recognition systems, Text-to-speech, text to speech systems, pronunciation trainers, and Computer-assisted language learning, second language learning systems. List __FORCETOC__ The actual table with information about the different databases is shown in Table 2. Legend In the table of non-native databases some abbreviations for language names are used. They are listed in Table 1. Table 2 gives the following information about each corpus: The name of the corpus, the institution where the corpus can be obtained, or at least further information should be available, the language which was actually spoken by the speakers, the number of speakers, the native language of the speakers, the total amount of non-native utterances the corpus contains, the duration in hours of the non-native part, the date ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Speech Corpus
A speech corpus (or spoken corpus) is a database of speech audio files and text transcriptions. In speech technology, speech corpora are used, among other things, to create acoustic models (which can then be used with a speech recognition or speaker identification engine). In linguistics, spoken corpora are used to do research into phonetic, conversation analysis, dialectology and other fields. A corpus is one such database. Corpora is the plural of corpus (i.e. it is many such databases). There are two types of Speech Corpora: # Read Speech – which includes: #* Book excerpts #* Broadcast news #* Lists of words #* Sequences of numbers # Spontaneous Speech – which includes: #* Dialogs – between two or more people (includes meetings; one such corpus is the KEC); #* Narratives – a person telling a story (one such corpus is the Buckeye Corpus); #* Map-tasks – one person explains a route on a map to another; #* Appointment-tasks – two people try to find a common meeti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Non-native Pronunciations Of English
Non-native pronunciations of English result from the common linguistic phenomenon in which non-native users of any language tend to carry the intonation, phonological processes and pronunciation rules from their first language or first languages into their English speech. They may also create innovative pronunciations for English sounds not found in the speaker's first language. Overview The speech of non-native English speakers may exhibit pronunciation characteristics that result from their imperfectly learning the sound system of English, either by transferring the phonological rules from their mother tongue into their English speech ("interference") or through implementing strategies similar to those used in primary language acquisition. They may also create innovative pronunciations for English sounds not found in the speaker's first language. The age at which speakers begin to immerse themselves into a language (such as English) is linked to the degree to which native s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Automatic Speech Recognition
Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers with the main benefit of searchability. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis. Some speech recognition systems require "training" (also called "enrollment") where an individual speaker reads text or isolated vocabulary into the system. The system analyzes the person's specific voice and uses it to fine-tune the recognition of that person's speech, resulting in increased accuracy. Systems that do not use training are called "speaker-independent" systems. Systems that use training are called "speaker dependent". Speech recognition ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Text-to-speech
Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products. A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic transcriptions into speech. The reverse process is speech recognition. Synthesized speech can be created by concatenating pieces of recorded speech that are stored in a database. Systems differ in the size of the stored speech units; a system that stores phones or diphones provides the largest output range, but may lack clarity. For specific usage domains, the storage of entire words or sentences allows for high-quality output. Alternatively, a synthesizer can incorporate a model of the vocal tract and other human voice characteristics to create a completely "synthetic" voice output. The quality of a speech synthesizer is judged by its similarity to ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer-assisted Language Learning
Computer-assisted language learning (CALL), British, or Computer-Aided Instruction (CAI)/Computer-Aided Language Instruction (CALI), American, is briefly defined in a seminal work by Levy (1997: p. 1) as "the search for and study of applications of the computer in language teaching and learning".Levy M. (1997) ''CALL: context and conceptualisation'', Oxford: Oxford University Press. CALL embraces a wide range of information and communications technology applications and approaches to teaching and learning foreign languages, from the "traditional" drill-and-practice programs that characterised CALL in the 1960s and 1970s to more recent manifestations of CALL, e.g. as used in a virtual learning environment and Web-based distance learning. It also extends to the use of corpora and concordancers, interactive whiteboards,Schmid Euline Cutrim (2009) ''Interactive whiteboard technology in the language classroom: exploring new pedagogical opportunities'', Saarbrücken, Germany: VDM V ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ICASSP
ICASSP, the International Conference on Acoustics, Speech, and Signal Processing, is an annual flagship conference organized of IEEE Signal Processing Society. All papers included in its proceedings have been indexed by Ei Compendex. The first ICASSP was held in 1976 in Philadelphia, Pennsylvania based on the success of a conference in Massachusetts four years earlier that had focused specifically on speech signals. As ranked by Google Scholar's h-index The ''h''-index is an author-level metric that measures both the productivity and citation impact of the publications, initially used for an individual scientist or scholar. The ''h''-index correlates with obvious success indicators such as ... metric in 2016, ICASSP has the highest h-index of any conference in Signal Processing field. Also, It is considered a high level conference in signal processing and, for example, obtained an 'A1' rating from the Brazilian ministry of education based on its H-index. References ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lori Lamel
Lori Faith Lamel is a speech processing researcher known for her work with the TIMIT corpus of American English speech and for her work on voice activity detection, speaker recognition, and other non-linguistic inferences from speech signals. She works for the French National Centre for Scientific Research (CNRS) as a senior research scientist in the Spoken Language Processing Group of the Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur. Education and career Lamel was a student at the Massachusetts Institute of Technology (MIT), where she earned bachelor's and master's degrees in electrical engineering and computer science in 1980 as a co-op student with Bell Labs. She earned her Ph.D. at MIT in 1988, with the dissertation ''Formalizing Knowledge used in Spectrogram Reading: Acoustic and perceptual evidence from stops'' supervised by Victor Zue. She completed a habilitation in 2004 at Paris-Sud University. She was a visiting researcher at CNRS in 198 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
English As A Second Or Foreign Language
English as a second or foreign language is the use of English by speakers with different native languages. Language education for people learning English may be known as English as a second language (ESL), English as a foreign language (EFL), English as an additional language (EAL), English as a New Language (ENL), or English for speakers of other languages (ESOL). The aspect in which ESL is taught is referred to as teaching English as a foreign language (TEFL), teaching English as a second language (TESL) or teaching English to speakers of other languages (TESOL). Technically, TEFL refers to English language teaching in a country where English is not the official language, TESL refers to teaching English to non-native English speakers in a native English-speaking country and TESOL covers both. In practice, however, each of these terms tends to be used more generically across the full field. TEFL is more widely used in the UK and TESL or TESOL in the US. The term "ESL" has ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Speech Recognition
Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers with the main benefit of searchability. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis. Some speech recognition systems require "training" (also called "enrollment") where an individual speaker reads text or isolated vocabulary into the system. The system analyzes the person's specific voice and uses it to fine-tune the recognition of that person's speech, resulting in increased accuracy. Systems that do not use training are called "speaker-independent" systems. Systems that use training are called "speaker dependent". Speech recognition ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
