@InProceedings{Fromont2026_1281,
<br/>   author = {Robert Fromont and Jennifer Hay and Daniel Duran and Allie Osborne and Melanie Weirich and Miriam Oschkinat and Stefanie Jannedy},
<br/>   booktitle = {Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2026, Tagungsband der 37. Konferenz},
<br/>   title = {Evaluating full automation of formant extraction in the German Plapper Corpus},
<br/>   year = {2026},
<br/>   editor = {Günther Wirsching},
<br/>   month = mar,
<br/>   pages = {78--85},
<br/>   publisher = {TUDpress, Dresden},
<br/>   abstract  = {We have collected over thirteen thousand recordings of German sentence readings elicited via the Plapper app as part of a citizen science project. However, manual correction of transcripts and phone alignments is a bottleneck for sociolinguistic study of these recordings, with less than 10% of recordings processed so far, as data collection continues. We evaluate the possibility of fully automating the transcription and alignment of the Plapper corpus. Two automated transcription processes were tried and their target-word error rates compared; BAS ASR Web Service, and using the text prompt read by the participants as the transcript. Furthermore two forced alignment systems were evaluated: WebMAUS and the Montreal Forced Aligner. Their outputs were compared with manually corrected alignments, using both overlap rate to compare them temporally, and correlation of resulting formant measurements. We found that using prompt text as a transcript is more accurate than ASR, and that both forced aligners produced sufficiently trustworthy alignments, with resulting formant measurements that correlated highly with those generated from manually corrected alignments.},
<br/>   isbn = {978-3-95908-834-3},
<br/>   issn = {0940-6832},
<br/>   keywords = {Speech Analysis I},
<br/>   url = {https://www.essv.de/pdf/2026_78_85.pdf},
<br/>}