Update README.md

README.md

@@ -36,13 +36,15 @@
 
 ### Dataset Summary
 
-The dataset comprises audio recordings featuring spontaneous speech from young Swiss learners of English, specifically from students in grades 4 to 6. The audio data was collected during engaging language activities designed to elicit natural speech patterns and includes corresponding verbatim transcripts where learners' errors are annotated. The learners participated in a variety of tasks such as role plays, guessing games, and mock interviews, providing a rich source of authentic conversational data.
-
+This dataset contains audio recordings of spontaneous speech by young learners of English in Switzerland.
+The recordings capture various language learning tasks designed to elicit authentic communication from the students.
+The dataset includes detailed verbatim transcriptions with annotations for errors made by the learners.
 The transcripts were prepared by a professional transcription service, and each recording was associated with detailed metadata, including school grade, recording conditions, and error annotations.
 
 Access to the dataset is regulated to ensure the confidentiality and ethical use of the sensitive data.
 To use the ChaLL dataset, you need to download it manually. Follow the instructions provided (**yet to be detailed**) for downloading the data. Once you have downloaded the files, please extract all files into a single folder. 
 
+
 Examples in this dataset are generated using the `soundfile` library (for reading and chunking). To handle the audio data correctly, you need to install the soundfile library.
 
 ```shell
@@ -80,37 +82,51 @@ A typical data instance in this dataset include an audio file, its full transcri
 
 ### Data Splits
 
-[More Information Needed]
+#### `asr_acl`
+
+For the experiments in this paper, we split the dataset into five distinct folds of similar duration
+(about 16h each), where each class (and therefore also each speaker) occurs in only one fold.
+To simulate the use case of the ASR system being confronted with a new class of learners, each fold
+contains data from a mix of grades. The following figure visualises the duration and grade distribution of each fold.
+
+![Chall Folds](/chall_data_folds_v1.svg)
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-The dataset was curated to address the lack of resources for developing ASR systems that can handle the unique characteristics of children's speech, especially non-native English speakers, and to facilitate the development of educational tools that provide corrective feedback on language learning.
+The dataset was created to address the need for ASR systems that can handle children’s spontaneous speech 
+and preserve their errors to provide effective corrective feedback in language learning environments.
+
 
 ### Source Data
 
 #### Initial Data Collection and Normalization
 
-Audio recordings were collected in controlled environments mimicking naturalistic settings to elicit genuine conversational speech from children. The recordings were then annotated professionally to include detailed error tags.
+Audio data was collected from primary school students aged 9 to 14 years, performing language learning tasks in pairs, trios, or individually. The recordings were made at schools and universities, and detailed verbatim transcriptions were created by a transcription agency, following specific guidelines.
+
 
 #### Who are the source language producers?
 
-The language producers are Swiss children from grades 4 to 6, engaged in language learning activities designed to elicit natural speech.
+The source data producers include primary school students from German-speaking Switzerland, aged 9 to 14 years, participating in language learning activities.
 
 ### Annotations
 
 #### Annotation process
 
-[More Information Needed]
+The transcription and annotation process was outsourced to a transcription agency, following detailed guidelines for error annotation, 
+including symbols for grammatical, lexical, and pronunciation errors, as well as German word usage.
+
 
 #### Who are the annotators?
 
-Transcriptions and error annotations were performed by a professional service, following strict guidelines to ensure accuracy and consistency in error marking.
+The annotators were professionals from a transcription agency, trained according to specific guidelines provided by the project team.
 
 ### Personal and Sensitive Information
 
-The dataset contains audio recordings of children, and all personal identifiers have been removed to protect privacy. Access to the data is restricted and requires approval to ensure ethical use.
+The dataset contains audio recordings of minors.
+All data was collected with informed consent from legal guardians, and recordings are anonymized to protect the identities of the participants.
+
 
 ## Considerations for Using the Data
 
@@ -124,7 +140,8 @@ Given the specific demographic (Swiss German-speaking schoolchildren), the datas
 
 ### Other Known Limitations
 
-[More Information Needed]
+The outsourcing of transcription and error annotations always poses a risk of yielding erroneous data, since most
+transcribers are not trained in error annotation.
 
 ## Additional Information
 
@@ -138,7 +155,16 @@ The dataset was curated by researchers at PHZH, UZH and Zhaw, with collaboration
 
 ### Citation Information
 
-[More Information Needed]
+```bibtex
+@inproceedings{
+  anonymous2024errorpreserving,
+  title={Error-preserving Automatic Speech Recognition of Young English Learners' Language},
+  author={Anonymous},
+  booktitle={The 62nd Annual Meeting of the Association for Computational Linguistics},
+  year={2024},
+  url={https://openreview.net/forum?id=XPIwvlqIfI}
+}
+```
 
 ### Contributions