Panphon: a Resource for Mapping IPA Segments to Articulatory Feature Vectors
Total Page:16
File Type:pdf, Size:1020Kb

Load more
Recommended publications
-
Rule-Based Standard Arabic Phonetization at Phoneme, Allophone, and Syllable Level
Fadi Sindran, Firas Mualla, Tino Haderlein, Khaled Daqrouq & Elmar Nöth Rule-Based Standard Arabic Phonetization at Phoneme, Allophone, and Syllable Level Fadi Sindran [email protected] Faculty of Engineering Department of Computer Science /Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen, 91058, Germany Firas Mualla [email protected] Faculty of Engineering Department of Computer Science /Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen, 91058, Germany Tino Haderlein [email protected] Faculty of Engineering Department of Computer Science/Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen, 91058, Germany Khaled Daqrouq [email protected] Department of Electrical and Computer Engineering King Abdulaziz University, Jeddah, 22254, Saudi Arabia Elmar Nöth [email protected] Faculty of Engineering Department of Computer Science /Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen, 91058, Germany Abstract Phonetization is the transcription from written text into sounds. It is used in many natural language processing tasks, such as speech processing, speech synthesis, and computer-aided pronunciation assessment. A common phonetization approach is the use of letter-to-sound rules developed by linguists for the transcription from grapheme to sound. In this paper, we address the problem of rule-based phonetization of standard Arabic. 1The paper contributions can be summarized as follows: 1) Discussion of the transcription rules of standard Arabic which were used in literature on the phonemic and phonetic level. 2) Improvements of existing rules are suggested and new rules are introduced. Moreover, a comprehensive algorithm covering the phenomenon of pharyngealization in standard Arabic is proposed. -
Part 1: Introduction to The
PREVIEW OF THE IPA HANDBOOK Handbook of the International Phonetic Association: A guide to the use of the International Phonetic Alphabet PARTI Introduction to the IPA 1. What is the International Phonetic Alphabet? The aim of the International Phonetic Association is to promote the scientific study of phonetics and the various practical applications of that science. For both these it is necessary to have a consistent way of representing the sounds of language in written form. From its foundation in 1886 the Association has been concerned to develop a system of notation which would be convenient to use, but comprehensive enough to cope with the wide variety of sounds found in the languages of the world; and to encourage the use of thjs notation as widely as possible among those concerned with language. The system is generally known as the International Phonetic Alphabet. Both the Association and its Alphabet are widely referred to by the abbreviation IPA, but here 'IPA' will be used only for the Alphabet. The IPA is based on the Roman alphabet, which has the advantage of being widely familiar, but also includes letters and additional symbols from a variety of other sources. These additions are necessary because the variety of sounds in languages is much greater than the number of letters in the Roman alphabet. The use of sequences of phonetic symbols to represent speech is known as transcription. The IPA can be used for many different purposes. For instance, it can be used as a way to show pronunciation in a dictionary, to record a language in linguistic fieldwork, to form the basis of a writing system for a language, or to annotate acoustic and other displays in the analysis of speech. -
Issues in the Distribution of the Glottal Stop
Theoretical Issues in the Representation of the Glottal Stop in Blackfoot* Tyler Peterson University of British Columbia 1.0 Introduction This working paper examines the phonemic and phonetic status and distribution of the glottal stop in Blackfoot.1 Observe the phonemic distribution (1), four phonological operations (2), and three surface realizations (3) of the glottal stop: (1) a. otsi ‘to swim’ c. otsi/ ‘to splash with water’ b. o/tsi ‘to take’ (2) a. Metathesis: V/VC ® VV/C nitáó/mai/takiwa nit-á/-omai/takiwa 1-INCHOAT-believe ‘now I believe’ b. Metathesis ® Deletion: V/VùC ® VVù/C ® VVùC kátaookaawaatsi káta/-ookaa-waatsi INTERROG-sponsor.sundance-3s.NONAFFIRM ‘Did she sponsor a sundance?’ (Frantz, 1997: 154) c. Metathesis ® Degemination: V/V/C ® VV//C ® VV/C áó/tooyiniki á/-o/too-yiniki INCHOAT-arrive(AI)-1s/2s ‘when I/you arrive’ d. Metathesis ® Deletion ® V-lengthening: V/VC ® VV/C ® VVùC kátaoottakiwaatsi káta/-ottaki-waatsi INTEROG-bartender-3s.NONAFFIRM ‘Is he a bartender?’ (Frantz, 1997) (3) Surface realizations: [V/C] ~ [VV0C] ~ [VùC] aikai/ni ‘He dies’ a. [aIkaI/ni] b. [aIkaII0ni] c. [aIkajni] The glottal stop appears to have a unique status within the Blackfoot consonant inventory. The examples in (1) (and §2.1 below) suggest that it appears as a fully contrastive phoneme in the language. However, the glottal stop is put through variety of phonological processes (metathesis, syncope and degemination) that no other consonant in the language is subject to. Also, it has a variety of surfaces realizations in the form of glottalization on an adjacent vowel (cf. -
Lecture # 07 (Phonetics)
Phonetics Phonetics (Introduction), Syllables, - text-to-speech recognition, - Onset, nucleus - Phones, - Coda, Rime, Speech sounds and Phonetic - Consonants and vowels, transcription, Phonological Categories and - International Phonetic Alphabet Pronunciation variation, (IPA), - ARPAbet, - Phonetic features, Articulatory Phonetics, - Predicting Phonetic variation, - The Vocal organs, - Factors Influencing Phonetic - Consonants: Place of Articulation, variation, - Consonants: Manner of Articulation, - Vowels, - Syllables, @Copyrights: Natural Language Processing (NLP) Organized by Dr. Ahmad Jalal (http://portals.au.edu.pk/imc/) 1. Phonetics (Introduction) “ What is the proper pronunciation of word “Special”” Text-to-speech conversation (converting strings of text words into acoustic waveforms). “Phonics” methods of teaching to children; - is first glance like a purely modern educational debate. Phonetics is the study of linguistic sounds, - how they are produced by the articulators of the human vocal tract, - how they are realized acoustically, - and how this acoustic realization can be digitized and processed. A key element of both speech recognition and text-to-speech systems: - how words are pronounced in terms of individual speech units called phones. @Copyrights: Natural Language Processing (NLP) Organized by Dr. Ahmad Jalal (http://portals.au.edu.pk/imc/) 2. Speech Sounds and Phonetic Transcription The study of the pronunciation of words is part of the field of phonetics, We model the pronunciation of a word as a string of symbols which represent phones or segments. - A phone is a speech sound; - phones are represented with phonetic symbols that bear some resemblance to a letter. We use 2 different alphabets for describing phones as; (1) The International Phonetic Alphabet (IPA) - is an evolving standard originally developed by the International Phonetic Association in 1888 with the goal of transcribing the sounds of all human languages. -
The Primary Laryngeal in Uralic and Beyond
JUHA JANHUNEN THE PRIMARY LARYNGEAL IN URALIC AND BEYOND 1. Laryngeals in synchronic systems Many languages, though not all, have in their phonemic inventory one or more segments that may be classifi ed as “laryngeals”, that is, as segments belonging to what may be called the “laryngeal range” of the consonantal paradigm. In a narrow sense of the term, the laryngeal range would comprise of only seg- ments produced with a laryngeal (glottal) primary articulation, but in a broad understanding this may be conveniently defi ned as comprising of any velar or postvelar consonants that are distinct from the basic velar stops [k ɡ] in terms of either the place or manner of articulation. Most laryngeals are continuants produced as either fricatives (with a relatively strong frication) or spirants (with a relatively weak frication) in the velar, uvular, pharyngeal, epiglottal or glottal zones of the vocal tract (cf. e.g. Ladefoged & Maddieson 1996: 39–46), though there are also non-continuant laryngeals produced as stops or affricates in the uvular and glottal zones. With the exception of the glottal stop [ʔ], which is pro- duced with a closure of the vocal chords, the segments classifi able as laryngeals can be either voiced or voiceless. It is synchronically typical of laryngeals that they often involve a consider- able lability of the articulatory parameters. Most languages have a very limited set of segments classifi able as laryngeals, which is why features such as place of articulation and voice are rarely fully exploited to distinguish one laryngeal from another. Many languages have only one segment in the laryngeal range, in which case its phonetic value can vary within a broad range. -
Towards Zero-Shot Learning for Automatic Phonemic Transcription
The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) Towards Zero-Shot Learning for Automatic Phonemic Transcription Xinjian Li, Siddharth Dalmia, David R. Mortensen, Juncheng Li, Alan W Black, Florian Metze Language Technologies Institute, School of Computer Science Carnegie Mellon University {xinjianl, sdalmia, dmortens, junchenl, awb, fmetze}@cs.cmu.edu Abstract Hermann and Goldwater 2018), which typically uses an un- supervised technique to learn representations which can be Automatic phonemic transcription tools are useful for low- resource language documentation. However, due to the lack used towards speech processing tasks. of training sets, only a tiny fraction of languages have phone- However, those unsupervised approaches could not gener- mic transcription tools. Fortunately, multilingual acoustic ate phonemes directly and there has been few works study- modeling provides a solution given limited audio training ing zero-shot learning for unseen phonemes transcription, data. A more challenging problem is to build phonemic tran- which consist of learning an acoustic model without any au- scribers for languages with zero training data. The difficulty dio data or text data for a given target language and unseen of this task is that phoneme inventories often differ between phonemes. In this work, we aim to solve this problem to the training languages and the target language, making it in- transcribe unseen phonemes for unseen languages without feasible to recognize unseen phonemes. In this work, we ad- dress this problem by adopting the idea of zero-shot learning. considering any target data, audio or text. Our model is able to recognize unseen phonemes in the tar- The prediction of unseen objects has been studied for a get language without any training data. -
UC Berkeley Dissertations, Department of Linguistics
UC Berkeley Dissertations, Department of Linguistics Title Relationship between Perceptual Accuracy and Information Measures: A cross-linguistic Study Permalink https://escholarship.org/uc/item/7tx5t8bt Author Kang, Shinae Publication Date 2015 eScholarship.org Powered by the California Digital Library University of California Relationship between perceptual accuracy and information measures: A cross-linguistic study by Shinae Kang A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Linguistics in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Keith A. Johnson, Chair Professor Sharon Inkelas Professor Susan S. Lin Professor Robert T. Knight Fall 2015 Relationship between perceptual accuracy and information measures: A cross-linguistic study Copyright 2015 by Shinae Kang 1 Abstract Relationship between perceptual accuracy and information measures: A cross-linguistic study by Shinae Kang Doctor of Philosophy in Linguistics University of California, Berkeley Professor Keith A. Johnson, Chair The current dissertation studies how the information conveyed by different speech el- ements of English, Japanese and Korean correlates with perceptual accuracy. Two well- established information measures are used: weighted negative contextual predictability (in- formativity) of a speech element; and the contribution of a speech element to syllable differ- entiation, or functional load. This dissertation finds that the correlation between information and perceptual accuracy differs depending on both the type of information measure and the language of the listener. To compute the information measures, Chapter 2 introduces a new corpus consisting of all the possible syllables for each of the three languages. The chapter shows that the two information measures are inversely correlated. -
Velar Segments in Old English and Old Irish
In: Jacek Fisiak (ed.) Proceedings of the Sixth International Conference on Historical Linguistics. Amsterdam: John Benjamins, 1985, 267-79. Velar segments in Old English and Old Irish Raymond Hickey University of Bonn The purpose of this paper is to look at a section of the phoneme inventories of the oldest attested stage of English and Irish, velar segments, to see how they are manifested phonetically and to consider how they relate to each other on the phonological level. The reason I have chosen to look at two languages is that it is precisely when one compares two language systems that one notices that structural differences between languages on one level will be correlated by differences on other levels demonstrating their interrelatedness. Furthermore it is necessary to view segments on a given level in relation to other segments. The group under consideration here is just one of several groups. Velar segments viewed within the phonological system of both Old English and Old Irish cor relate with three other major groups, defined by place of articulation: palatals, dentals, and labials. The relationship between these groups is not the same in each language for reasons which are morphological: in Old Irish changes in grammatical category are frequently indicated by palatalizing a final non-palatal segment (labial, dental, or velar). The same function in Old English is fulfilled by suffixes and /or prefixes. This has meant that for Old English the phonetically natural and lower-level alternation of velar elements with palatal elements in a palatal environ ment was to be found whereas in Old Irish this alternation had been denaturalized and had lost its automatic character. -
Package 'Phontools'
Package ‘phonTools’ July 31, 2015 Title Tools for Phonetic and Acoustic Analyses Version 0.2-2.1 Date 2015-07-30 Author Santiago Barreda Maintainer Santiago Barreda <[email protected]> Depends R (>= 2.15) Description Contains tools for the organization, display, and analysis of the sorts of data fre- quently encountered in phonetics research and experimentation, including the easy cre- ation of IPA vowel plots, and the creation and manipulation of WAVE audio files. License BSD_2_clause + file LICENSE URL http://www.santiagobarreda.com/rscripts.html NeedsCompilation no Repository CRAN Date/Publication 2015-07-31 01:00:47 R topics documented: a96..............................................3 b95 .............................................4 combocalc . .4 createtemplate . .5 errorbars . .6 f73..............................................7 f99..............................................8 fastacf . .9 Ffilter . 10 findformants . 11 FIRfilter . 13 formanttrack . 14 freqresponse . 16 h95 ............................................. 17 hotelling.test . 18 1 2 R topics documented: imputeformants . 20 interpolate . 21 ldboundary . 22 ldclassify . 23 loadsound . 25 loadtable . 26 lpc.............................................. 26 makeFIR . 27 makesound . 29 multiplot . 30 normalize . 31 normalize.compare . 33 ntypes . 34 p73 ............................................. 35 pb52............................................. 36 peakfind . 37 phasor . 37 pickIPA . 38 pitchtrack . 40 playsound . 41 polezero . 42 powertrack . 43 preemphasis . 44 -
Multilingual Speech Recognition for Selected West-European Languages
master’s thesis Multilingual Speech Recognition for Selected West-European Languages Bc. Gloria María Montoya Gómez May 25, 2018 advisor: Doc. Ing. Petr Pollák, CSc. Czech Technical University in Prague Faculty of Electrical Engineering, Department of Circuit Theory Acknowledgement I would like to thank my advisor, Doc. Ing. Petr Pollák, CSc. I was very privileged to have him as my mentor. Pollák was always friendly and patient to give me his knowl- edgeable advise and encouragement during my study at Czech Technical University in Prague. His high standards on quality taught me how to do good scientific work, write, and present ideas. Declaration I declare that I worked out the presented thesis independently and I quoted all used sources of information in accord with Methodical instructions about ethical principles for writing academic thesis. iii Abstract Hlavním cílem předložené práce bylo vytvoření první verze multilingválního rozpozná- vače řeči pro vybrané 4 západoevropské jazyky. Klíčovým úkolem této práce bylo de- finovat vztahy mezi subslovními akustickými elementy napříč jednotlivými jazyky při tvorbě automatického rozpoznávače řeči pro více jazyků. Vytvořený multilingvální sys- tém pokrývá aktuálně následující jazyky: angličtinu, němčinu, portugalštinu a španěl- štinu. Jelikož dostupná fonetická reprezentace hlásek pro jednotlivé jazyky byla různá podle použitých zdrojových dat, prvním krokem této práce bylo její sjednocení a vy- tvoření sdílené fonetické reprezentace na bázi abecedy X-SAMPA. Pokud jsou dále acoustické subslovní elementy reprezentovány sdílenými skrytými Markovovy modely, případný nedostatek zdrojových dat pro trénováni může být pokryt z jiných jazyků. Dalším krokem byla vlastní realizace multilingválního systému pomocí nástrojové sady KALDI. Použité jazykové modely byly na bázi zredukovaných trigramových modelů zís- kaných z veřejně dostupých zdrojů. -
Phonemic Similarity Metrics to Compare Pronunciation Methods
Phonemic Similarity Metrics to Compare Pronunciation Methods Ben Hixon1, Eric Schneider1, Susan L. Epstein1,2 1 Department of Computer Science, Hunter College of The City University of New York 2 Department of Computer Science, The Graduate Center of The City University of New York [email protected], [email protected], [email protected] error rate. The minimum number of insertions, deletions and Abstract substitutions required for transformation of one sequence into As graphemetophoneme methods proliferate, their careful another is the Levenshtein distance [3]. Phoneme error rate evaluation becomes increasingly important. This paper ex (PER) is the Levenshtein distance between a predicted pro plores a variety of metrics to compare the automatic pronunci nunciation and the reference pronunciation, divided by the ation methods of three freelyavailable graphemetophoneme number of phonemes in the reference pronunciation. Word er packages on a large dictionary. Two metrics, presented here ror rate (WER) is the proportion of predicted pronunciations for the first time, rely upon a novel weighted phonemic substi with at least one phoneme error to the total number of pronun tution matrix constructed from substitution frequencies in a ciations. Neither WER nor PER, however, is a sufficiently collection of trusted alternate pronunciations. These new met sensitive measurement of the distance between pronunciations. rics are sensitive to the degree of mutability among phonemes. Consider, for example, two pronunciation pairs that use the An alignment tool uses this matrix to compare phoneme sub ARPAbet phoneme set [4]: stitutions between pairs of pronunciations. S OW D AH S OW D AH Index Terms: graphemetophoneme, edit distance, substitu S OW D AA T AY B L tion matrix, phonetic distance measures On the left are two reasonable pronunciations for the English word “soda,” while the pair on the right compares a pronuncia 1. -
Dynamic Modeling for Chinese Shaanxi Xi'an Dialect Visual
UNIVERSITY OF MISKOLC FACULTY OF MECHANICAL ENGINEERING AND INFORMATICS Dynamic Modeling for Chinese Shaanxi Xi’an Dialect Visual Speech Summary of PhD dissertation Lu Zhao Information Science ‘JÓZSEF HATVANY’ DOCTORAL SCHOOL OF INFORMATION SCIENCE, ENGINEERING AND TECHNOLOGY ACADEMIC SUPERVISOR Dr. László Czap Miskolc 2020 Content Introduction ............................................................................................................. 1 Chapter 1 Phonetic Aspects of the Chinese Shaanxi Xi’an Dialect ......................... 3 1.1. Design of the Chinese Shaanxi Xi’an Dialect X-SAMPA ..................... 3 1.2. Theoretical method of transcription from the Chinese character to X-SAMPA .................................................................................................... 5 Chapter 2 Visemes of the Chinese Shaanxi Xi’an Dialect....................................... 6 2.1. Quantitative description of lip static visemes ........................................ 6 2.2. Analysis of static tongue visemes of the Chinese Shaanxi Xi’an Dialect ...................................................................................................................... 7 Chapter 3 Dynamic Modeling of the Chinese Shaanxi Xi’an Dialect Speech ....... 11 3.1. The interaction between phonemes and the corresponding lip shape ... 11 3.2. Dynamic tongue viseme classification ................................................. 12 3.3. Results of face animation on the Chinese Shaanxi Xi’an Dialect talking head ...........................................................................................................