An orthography is a set of conventions for writing a language, including norms of spelling, hyphenation, capitalization, word boundaries, emphasis, and punctuation.
In phonology and linguistics, a phoneme is a unit of phone that can distinguish one word from another in a particular language.
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.
Transcription in the linguistic sense is the systematic representation of spoken language in written form. The source can either be utterances or preexisting text in another writing system.
A phonemic orthography is an orthography in which the graphemes correspond to the phonemes of the language. Natural languages rarely have perfectly phonemic orthographies; a high degree of grapheme–phoneme correspondence can be expected in orthographies based on alphabetic writing systems, but they differ in how complete this correspondence is. English orthography, for example, is alphabetic but highly nonphonemic; it was once mostly phonemic during the Middle English stage, when the modern spellings originated, but spoken English changed rapidly while the orthography was much more stable, resulting in the modern nonphonemic situation. On the contrary the Albanian, Serbian/Croatian/Bosnian/Montenegrin, Romanian, Italian, Turkish, Spanish, Finnish, Czech, Latvian, Esperanto, Korean and Swahili orthographic systems come much closer to being consistent phonemic representations.
The British National Corpus (BNC) is a 100-million-word text corpus of samples of written and spoken English from a wide range of sources. The corpus covers British English of the late 20th century from a wide variety of genres, with the intention that it be a representative sample of spoken and written British English of that time. It is used in corpus linguistics for analysis of corpora.
MBROLA is speech synthesis software as a worldwide collaborative project. The MBROLA project web page provides diphone databases for many spoken languages.
A speech 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. In linguistics, spoken corpora are used to do research into phonetic, conversation analysis, dialectology and other fields.
The CMU Pronouncing Dictionary is an open-source pronouncing dictionary originally created by the Speech Group at Carnegie Mellon University (CMU) for use in speech recognition research.
Audio mining is a technique by which the content of an audio signal can be automatically analyzed and searched. It is most commonly used in the field of automatic speech recognition, where the analysis tries to identify any speech within the audio. The term ‘audio mining’ is sometimes used interchangeably with audio indexing, phonetic searching, phonetic indexing, speech indexing, audio analytics, speech analytics, word spotting, and information retrieval. Audio indexing, however, is mostly used to describe the pre-process of audio mining, in which the audio file is broken down into a searchable index of words.
The International Corpus of English(ICE) is a set of corpora representing varieties of English from around the world. Over twenty countries or groups of countries where English is the first language or an official second language are included.
eSpeak is a free and open-source, cross-platform, compact, software speech synthesizer. It uses a formant synthesis method, providing many languages in a relatively small file size. eSpeakNG is a continuation of the original developer's project with more feedback from native speakers.
The Survey of English Usage was the first research centre in Europe to carry out research with corpora. The Survey is based in the Department of English Language and Literature at University College London.
The Buckeye Corpus of conversational speech is a speech corpus created by a team of linguists and psychologists at Ohio State University led by Prof. Mark Pitt. It contains high-quality recordings from 40 speakers in Columbus, Ohio conversing freely with an interviewer. The interviewer's voice is heard only faintly in the background of these recordings. The sessions were conducted as Sociolinguistics interviews, and are essentially monologues. The speech has been orthographically transcribed and phonetically labeled. The audio and text files, together with time-aligned phonetic labels, are stored in a format for use with speech analysis software. Software for searching the transcription files is also available at the project web site. The corpus is available to researchers in academics and industry.
UTAU is a Japanese singing synthesizer application created by Ameya/Ayame (飴屋／菖蒲). This program is similar to the VOCALOID software, with the difference being it is shareware instead of under a third party licensing.
Speech translation is the process by which conversational spoken phrases are instantly translated and spoken aloud in a second language. This differs from phrase translation, which is where the system only translates a fixed and finite set of phrases that have been manually entered into the system. Speech translation technology enables speakers of different languages to communicate. It thus is of tremendous value for humankind in terms of science, cross-cultural exchange and global business.
The Spoken English Corpus (SEC) is a speech corpus collection of recordings of spoken British English compiled during 1984–7. The corpus manual can be found on ICAME.
The Arabic Speech Corpus is a Modern Standard Arabic (MSA) speech corpus for speech synthesis. The corpus contains phonetic and orthographic transcriptions of more than 3.7 hours of MSA speech aligned with recorded speech on the phoneme level. The annotations include word stress marks on the individual phonemes.
The PCVC Speech Dataset is a Modern Persian speech corpus for speech recognition and also speaker recognition. The dataset contains sound samples of Modern Persian combination of vowel and consonant phonemes from different speakers. Every sound sample contains just one consonant and one vowel So it is somehow labeled in phoneme level. This dataset consists of 23 Persian consonants and 6 vowels. The sound samples are all possible combinations of vowels and consonants. The sample rate of all speech samples is 48000 which means there are 48000 sound samples in every 1 second. Every sound sample starts with consonant then continues with vowel. In each sample, in average, 0.5 second of each sample is speech and the rest is silence. Each sound sample ends with silence. All of sound samples are denoised with "Adaptive noise reduction" algorithm. Compared to Farsdat speech dataset and Persian speech corpus it is more easy to use because it is prepared in .mat data files. Also it is more based on phoneme based separation and all samples are denoised.
