Researching and assessing speech and language in a digital world
Analyzing natural speech and language samples of children is a well-known source of insights when conducting research in the field of speech and language acquisition. The process of collecting, manual transcription and analysis of these data however is extremely time-consuming and costly. Because of that, the data basis for many milestones in speech and language development is scarce due to small sample sizes.
Meanwhile speech recognition and processing technology has been developed to a point where use for research purposes in linguistics and speech-language-pathology seems possible. For the recognition of adult language, technology has evolved to mainstream applications like Siri, Alexa or Dragon Speech. However processing child utterances is much more challenging due to their acoustic and language properties.
The TALC project develops a hard- and software tool which enables recording as well as (semi)automatized transcription and linguistic analysis of natural speech samples. Researching speech and language development is transformed digitally on the interface of linguistics, computer linguistics, speech and language pathology / pedagogy and computer science:
- Big data access is possible by making the process of recording, transcription and analysis more applicable
- Knowledge drawn from data is based on longer sequences of natural communication
- Transferring results into intervention is facilitated by analyzing individual environments for speech and language acquisition
- TALC data can provide an alternative in evaluating change in everyday communication (as demanded by the ICF)
TALC Project Status
TALC-LSA is undertaking two parallel project strands in Germany and South Africa. At both locations, collaborative teams from the disciplines of speech therapy, (computer) linguistics, and computer science/electrical engineering are engaged in the development of the requisite systems.
The pilot studies in both countries commenced in 2019. The development of TALC-LSA is currently underway in Germany with a focus on German-speaking children, with a secondary focus on multilingual children. The development is also underway in South Africa with a focus on Afrikaans. The South African team initiated the collection of data in other national languages in 2022. The initial focus of this project is on Sesotho sa Leboa and isiXhosa, with the latter in cooperation with Fort Hare University in the Eastern Cape. The TALC project in South Africa is being led by Professor Jeannie van der Linde of the University of Pretoria.
In Germany, the TALC software is scheduled to be piloted for the first time in a clinical setting for the healthcare sector in the TALC-CI subproject, which has commenced in 2023.
Since 2025, the Federal Ministry for Economic Affairs and Energy has provided funding for a period of two years to facilitate the transfer of research findings into practice in the education and health sectors as part of the EXIST funding line. The associated spin-off is entitled "Phonomatics".
Publications
2024
- Ehlert, H., van der Linde, J., Lüdtke, U. & Bornman, J. (2024). New directions in language sample analysis for multilingual contexts. In M. Bortz (ed.). A guide to global language assessment: A lifespan approach. p. 111-131. Taylor and Francis Inc., USA
2023
- Gebauer, C., Rumberg, L., Ehlert, H., Lüdtke, U. & Ostermann, J. (2023). Exploiting Diversity of Automatic Transcripts from Distinct Speech Recognition Techniques for Children’s Speech. Proceedings INTERSPEECH -- 24th Annual Conference of the International Speech Communication Association, August 2023, 4578-4582.
- Rumberg, L., Gebauer, C., Ehlert, H., Wallbaum, M., Lüdtke, U. & Ostermann, J. (accepted). Uncertainty Estimation for Connectionist Temporal Classification Based Automatic Speech Recognition. Proceedings INTERSPEECH -- 24th Annual Conference of the International Speech Communication Association, August 2023, 4583-4587.
- Lüdtke, U., Ehlert, H., Gaigulo, D., & Bornam, J. (2023). Research on the Methodology of LSA with Preschool Children: A Scoping Review. Clinical Archives of Communication Disorders, 8(2), 29-46.
- Ehlert, H., Beaulac, E., Wallbaum, M., Gebauer, C., Rumberg, L., Ostermann, J., & Lüdtke, U. (2023). Collecting and Annotating Natural Child Speech Data - Challenges and Interdisciplinary Perspectives. Elektronische Sprachsignalverarbeitung, Tagungsband der 34. Konferenz, München, März 2023, 72-78.
- Gebauer, C., Rumberg, L., & Ostermann, J. (2023). Pronunciation Modelling for Children's Speech. Elektronische Sprachsignalverarbeitung, Tagungsband der 34. Konferenz, München, März 2023, 79-86.
- Lüdtke, U., Bornman, J., de Wet, F., Heid, U., Ostermann, J., Rumberg, L., van der Linde, J., & Ehlert, H. (2023). Multi-disciplinary perspectives on automatic analysis of children's language samples: Where do we go from here? Folia Phoniatrica et Logopaedica, 75(1), 1-12. doi: 10.1159/000527427
2022
- Rumberg, L., Gebauer, C., Ehlert, H., Lüdtke, U. & Ostermann, J. (2022). Improving Phonetic Transcriptions of Children’s Speech by Pronunciation Modelling with Constrained CTC-Decoding. Proceedings INTERSPEECH -- 23th Annual Conference of the International Speech Communication Association, September 2022, 1357-1361.
2021
- Rumberg, L., Ehlert, H., Lüdtke, U. & Ostermann, J. (2021). Age-Invariant Training for End-to-End Child Speech Recognition using Adversarial Multi-Task Learning. Proceedings INTERSPEECH -- 22th Annual Conference of the International Speech Communication Association, August 2021, 3850-3854.