# Phonetic Segmentation of the UCLA Phonetics Lab Archive

arXiv: https://arxiv.org/abs/2403.19509 · HTML: https://mlsanity.com/paper/2403.19509/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 28 references that are in the map.
- First posted on arXiv 28 Mar 2024.

## Builds on (most cited first, 5 of 5)

- [Common Voice: A Massively-Multilingual Speech Corpus](https://mlsanity.com/paper/1912.06670/) (2019)
- [MLS: A Large-Scale Multilingual Dataset for Speech Research](https://mlsanity.com/paper/2012.03411/) (2020)
- [A Corpus for Large-Scale Phonetic Typology](https://mlsanity.com/paper/2005.13962/) (2020)
- [Hierarchical Softmax for End-to-End Low-resource Multilingual Speech Recognition](https://mlsanity.com/paper/2204.03855/) (2022)
- [What shall we do with an hour of data? Speech recognition for the un- and under-served languages of Common Voice](https://mlsanity.com/paper/2105.04674/) (2021)

## Built on by (most cited first, 9 of 9)

- [[b] = [d] - [t] + [p]: Self-supervised Speech Models Discover Phonological Vector Arithmetic](https://mlsanity.com/paper/2602.18899/) (2026)
- [Self-Supervised Speech Models Encode Phonetic Context via Position-dependent Orthogonal Subspaces](https://mlsanity.com/paper/2603.12642/) (2026)
- [An Empirical Recipe for Universal Phone Recognition](https://mlsanity.com/paper/2603.29042/) (2026)
- [PRiSM: Benchmarking Phone Realization in Speech Models](https://mlsanity.com/paper/2601.14046/) (2026)
- [HuPER: A Human-Inspired Framework for Phonetic Perception](https://mlsanity.com/paper/2602.01634/) (2026)
- [Efficiently Identifying Low-Quality Language Subsets in Multilingual Datasets: A Case Study on a Large-Scale Multilingual Audio Dataset](https://mlsanity.com/paper/2410.04292/) (2024)
- [Phone Segmentation and Recognition through Phonological Activation Mapping](https://mlsanity.com/paper/2607.09020/) (2026)
- [FuseAlign: Forced Alignment in the Wild](https://mlsanity.com/paper/2609.33650/) (2026)
- [Reconstructing the Vocal Tract with Differentiable Acoustic Simulation](https://mlsanity.com/paper/2609.36737/) (2026)

## Abstract (arXiv)

Research in speech technologies and comparative linguistics depends on access to diverse and accessible speech data. The UCLA Phonetics Lab Archive is one of the earliest multilingual speech corpora, with long-form audio recordings and phonetic transcriptions for 314 languages (Ladefoged et al., 2009). Recently, 95 of these languages were time-aligned with word-level phonetic transcriptions (Li et al., 2021). Here we present VoxAngeles, a corpus of audited phonetic transcriptions and phone-level alignments of the UCLA Phonetics Lab Archive, which uses the 95-language CMU re-release as our starting point. VoxAngeles also includes word- and phone-level segmentations from the original UCLA corpus, as well as phonetic measurements of word and phone durations, vowel formants, and vowel f0. This corpus enhances the usability of the original data, particularly for quantitative phonetic typology, as demonstrated through a case study of vowel intrinsic f0. We also discuss the utility of the VoxAngeles corpus for general research and pedagogy in crosslinguistic phonetics, as well as for low-resource and multilingual speech technologies. VoxAngeles is free to download and use under a CC-BY-NC 4.0 license.