Clearing the transcription hurdle in dialect corpus building : the corpus of Southern Dutch dialects as case-study

This paper discusses how the transcription hurdle in dialect corpus building can be cleared. While corpus analysis has strongly gained in popularity in linguistic research, dialect corpora are still relatively scarce. This scarcity can be attributed to several factors, one of which is the challenging nature of transcribing dialects, given a lack of both orthographic norms for many dialects and speech technological tools trained on dialect data. This paper addresses the questions (i) how dialects can be transcribed efficiently and (ii) whether speech technological tools can lighten the transcription work. These questions are tackled using the Southern Dutch dialects (SDDs) as case study, for which the usefulness of automatic speech recognition (ASR), respeaking, and forced alignment is considered. Tests with these tools indicate that dialects still constitute a major speech technological challenge. In the case of the SDDs, the decision was made to use speech technology only for the word-level segmentation of the audio files, as the transcription itself could not be sped up by ASR tools. The discussion does however indicate that the usefulness of ASR and other related tools for a dialect corpus project is strongly determined by the sound quality of the dialect recordings, the availability of statistical dialect-specific models, the degree of linguistic differentiation between the dialects and the standard language, and the goals the transcripts have to serve

Automatic Transcription of Northern Prinmi Oral Art: Approaches and Challenges to Automatic Speech Recognition for Language Documentation

One significant issue facing language documentation efforts is the transcription bottleneck: each documented recording must be transcribed and annotated, and these tasks are extremely labor intensive (Ćavar et al., 2016). Researchers have sought to accelerate these tasks with partial automation via forced alignment, natural language processing, and automatic speech recognition (ASR) (Neubig et al., 2020). Neural network—especially transformer-based—approaches have enabled large advances in ASR over the last decade. Models like XLSR-53 promise improved performance on under-resourced languages by leveraging massive data sets from many different languages (Conneau et al., 2020). This project extends these efforts to a novel context, applying XLSR-53 to Northern Prinmi, a Tibeto-Burman Qiangic language spoken in Southwest China (Daudey & Pincuo, 2020). Specifically, this thesis aims to answer two questions. First, is the XLSR-53 ASR model useful for first-pass transcription of oral art recordings from Northern Prinmi, an under-resourced tonal language? Second, does preprocessing target transcripts to combine grapheme clusters—multi-character representations of lexical tones and characters with modifying diacritics—into more phonologically salient units improve the model\u27s predictions? Results indicate that—with substantial adaptations—XLSR-53 will be useful for this task, and that preprocessing to combine grapheme clusters does improve model performance

A Phonetic, Phonological, and Morphosyntactic Analysis of the Mara Language

This thesis presents a linguistic analysis of the Mara language, a Tibeto-Burman language spoken in northwest Myanmar and in neighboring districts of India. Data has been gathered through interviews with a native speaker. The analysis includes a full phonetic segment inventory of the dialect and a phonological analysis of contrastive sounds and contextual variants. Sound files embedded in the document illustrate the phonetic system. Mara\u27s distinctive phonetic features include the loss of word-final consonants, a set of voiceless sonorants, pre- and post- aspirated nasals, and lowered and unlowered vowel pairs. The morphosyntax of Mara pronominal words demonstrates a split-ergative case marking pattern. A deictic hierarchy of pronominal words accounts for variations in pronominal word presence and order

Using forced alignment for sociophonetic research on a minority language

Until recently, large-scale phonetic analyses have been out of reach for under-documented languages, but with the advent of methodologies such as forced alignment, they have now become possible. This paper describes a methodology for applying forced alignment (using the Montreal Forced Aligner) to a speech corpus of Matukar Panau, a minority language spoken in Papua New Guinea. We obtained measurements for 68,785 vowel tokens, produced in both narrative and conversational data by 34 speakers. We examined the social conditioning on a subset of these vowels according to traditional sociolinguistic categories of age and gender, and also consider the impact of clan as a major axis of organization in this community. We show that there is a role for clan as a sociolinguistic factor in conditioning the variation observed

Variation in Traditional Cockney and Popular London Speech

In this paper I examine recordings of two elderly Londoners, one male and one female, in an attempt to show the range of variation that can be found in the traditional speech of London as regards typical features such as H-dropping, TH-fronting, T-glottalling and L-vocalization. The female speaker lacks some of the traits that are generally considered characteristic of Cockney. Keywords: English dialectology, English sociolinguistics, Cockney, Popular London speech

Profiling fluency: an analysis of individual variation in disfluencies in adult males

This document is the Accepted Manuscript version of the following article: Kirsty McDougall, and Martin Duckworth, ‘Profiling fluency: An analysis of individual variation in disfluencies in adult males’, Speech Communication, Vol. 95:16-27, December 2017, DOI: https://doi.org/10.1016/j.specom.2017.10.001. Under embargo. Embargo end date: 10 April 2019. This manuscript version is made available under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License CC BY NC-ND 4.0, (http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.Individual variation in non-fluency behaviour in normally fluent (NF) adults, is investigated. Differences among speakers in the usage of a range of features such as filled and silent pauses, sound prolongations, repetition of phrases, words or part-words, and self-interruptions is explored in the spontaneous speech of 20 male speakers of Standard Southern British English from the DyViS database. The speech analysed is semi-spontaneous, and taken from a simulated police interview task. A taxonomy of fluency features for forensic analysis (TOFFA) was applied to this speech data. The rate of occurrence of each feature per 100 syllables is calculated for each speaker. Results show that individuals vary considerably in the rates of these fluency features occurring in their speech and that between-speaker differences are present in the types of features speakers produce. Implications of the significance of these findings for forensic phonetics are discussed.Peer reviewe

An integrated FLEx–ELAN workflow for linguistic analysis with multiple transcriptions and translations and multiple participants

This paper presents a workflow integrating the linguistic software ELAN and FLEx. This workflow allows the user to move between these two software applications to refine the transcription, translation, and annotation of the speech of multiple participants. The workflow also enables the addition of multiple writing systems for vernacular and analysis languages. The paper is based on a manual that explains in a simple and visual manner how to achieve such a set-up in both ELAN and FLEx. The workflow allows language consultants to make changes and additions to transcriptions and translations in ELAN in a script and language that they are most comfortable with. In this way, the workflow fills a gap where language consultants with limited computer literacy and command of the major interface languages of software programmes can still work on the basic analysis of recordings of a language that they know well.National Foreign Language Resource Cente