Text-Speech Alignment: A Robin Hood Approach for Endangered Languages

Forced alignment automatically aligns audio recordings of spoken language with transcripts at the level of individual sounds, greatly reducing the time required to prepare data for linguistic analysis. However, existing algorithms are mostly trained on a few well-documented languages. We test the performance of three algorithms against manually aligned data on data from a highly endangered language. At least some tasks, unsupervised alignment (either based on English or trained from a small corpus) is sufficiently reliable for it to be used on legacy data for low-resource languages. Descriptive phonetic work on vowel inventories and prosody can be accurately captured by automatic alignment with minimal training data. Underutilized legacy data exist for many endangered languages. This creates both a need and an opportunity to leverage new technology

A Robin Hood approach to forced alignment: English-trained algorithms and their use on Australian languages

Forced alignment automatically aligns audio recordings of spoken language with transcripts at the segment level, greatly reducing the time required to prepare data for phonetic analysis. However, existing algorithms are mostly trained on a few well-documented languages. We test the performance of three algorithms against manually aligned data. For at least some tasks, unsupervised alignment (either based on English or trained from a small corpus) is sufficiently reliable for it to be used on legacy data for low-resource languages. Descriptive phonetic work on vowel inventories and prosody can be accurately captured by automatic alignment with minimal training data. Consonants provided significantly more challenges for forced alignment

Congruent aero-tactile stimuli bias perception of voicing continua.

Multimodal integration is the formation of a coherent percept from different sensory inputs such as vision, audition, and somatosensation. Most research on multimodal integration in speech perception has focused on audio-visual integration. In recent years, audio-tactile integration has also been investigated, and it has been established that puffs of air applied to the skin and timed with listening tasks shift the perception of voicing by naive listeners. The current study has replicated and extended these findings by testing the effect of air puffs on gradations of voice onset time along a continuum rather than the voiced and voiceless endpoints of the original work. Three continua were tested: bilabial ("pa/ba"), velar ("ka/ga"), and a vowel continuum ("head/hid") used as a control. The presence of air puffs was found to significantly increase the likelihood of choosing voiceless responses for the two VOT continua but had no effect on choices for the vowel continuum. Analysis of response times revealed that the presence of air puffs lengthened responses for intermediate (ambiguous) stimuli and shortened them for endpoint (non-ambiguous) stimuli. The slowest response times were observed for the intermediate steps for all three continua, but for the bilabial continuum this effect interacted with the presence of air puffs: responses were slower in the presence of air puffs, and faster in their absence. This suggests that during integration auditory and aero-tactile inputs are weighted differently by the perceptual system, with the latter exerting greater influence in those cases where the auditory cues for voicing are ambiguous