Update README.md with basic, high-level information

README.md

@@ -2,27 +2,30 @@
 annotations_creators:
 - expert-generated
 language:
-- pl
+- en
+- de
+- es
+- fr
+- it
 license:
 - mit
 multilinguality:
 - monolingual
-
 dataset_info:
-  - config_name: config
-    features:
-      - name: audio_id
-        dtype: string
-      - name: audio
-        dtype:
-          audio:
-            sampling_rate: 16000
-      - name: text
-        dtype: string
+- config_name: config
+  features:
+  - name: audio_id
+    dtype: string
+  - name: audio
+    dtype:
+      audio:
+        sampling_rate: 16000
+  - name: text
+    dtype: string
 ---
 
 
-# Dataset Card for [Dataset Name]
+# MOCKS dataset
 
 ## Table of Contents
 - [Table of Contents](#table-of-contents)
@@ -59,15 +62,36 @@ dataset_info:
 
 ### Dataset Summary
 
-[More Information Needed]
+Multilingual Open Custom Keyword Spotting Testset (MOCKS) is a comprehensive audio testset for evaluation and benchmarking
+Open-Vocabulary Keyword Spotting (OV-KWS) models. It supports multiple OV-KWS problems:
+both text-based and audio-based keyword spotting, as well as offline and online (streaming) modes. 
+It is based on the LibriSpeech and Mozilla Common Voice datasets and contains
+almost 50,000 keywords, with audio data available in English, French, German, Italian, and Spanish.
+The testset was generated using automatically generated alignments used for the extraction of parts of the recordings that were split into keywords and test samples.
+MOCKS contains both positive and negative examples selected based on phonetic transcriptions that are challenging and should allow for in-depth OV-KWS model evaluation. 
+
+Please refer to our [paper]() for further details.
+
+[More Information Needed - add link to paper]
 
 ### Supported Tasks and Leaderboards
 
-[More Information Needed]
+The MOCKS dataset can be used for Open-Vocabulary Keyword Spotting (OV-KWS) task. It supports two OV-KWS types:
+- Query-by-Text, where keyword is provided by text and needs to be detected on audio stream.
+- Query-by-Example, where keyword is provided with enrollment audio for detection on audio stream.
+
+It also allows for:
+- offline keyword detection, where test audio is trimed to contrain only keyword of interest.
+- online (streaming) keyword detection, where test audio have past and future context besides keyword of interest.
 
 ### Languages
 
-[More Information Needed]
+The MOCKS incorporates 5 languages:
+- English - primary and largest test set,
+- German,
+- Spanish,
+- French,
+- Italian.
 
 ## Dataset Structure
 
@@ -81,10 +105,25 @@ dataset_info:
 
 ### Data Splits
 
-[More Information Needed]
+The MOCKS testset is split by language, source dataset and OV-KWS type. Each split is divided into:
+- positive examples - test examples with true keyword, 5000-8000 keywords in each subset,
+- similar examples - test examples with similar phrases to keyword selected based on phonetic transcription distance,
+- different examples - test examples with completaly different prases.
+
+Each split also contains subset of whole data to allow faster evaluation.
 
 ## Dataset Creation
 
+The MOCKS testset was created from LibriSpeech and Mozilla Common Voice (MCV) datasets that are publicly available. To create it:
+- a [MFA](https://mfa-models.readthedocs.io/en/latest/acoustic/index.html) with publicly available models was used to extract word-level alignments,
+- an internally-developed, rule-based grapheme-to-phoneme (G2P) algorithm was used to prepare phonetic transcriptions for each sample.
+
+The data is stored in a 16-bit, single-channel WAV format. 16kHz sampling rate is used for LibriSpeech based testset
+and 48kHz sampling rate for MCV based testset.
+
+The offline testset contains additional 0.1 second at the beginning and end of extracted audio sample to mitigate the cut-speech effect.
+The online version contrains additional 1 second or so at the beginning and end of extracted audio sample.
+
 ### Curation Rationale
 
 [More Information Needed]
@@ -121,7 +160,7 @@ dataset_info:
 
 ### Discussion of Biases
 
-[More Information Needed]
+The MOCKS testset is speaker gender balanced.
 
 ### Other Known Limitations
 
@@ -139,7 +178,14 @@ dataset_info:
 
 ### Citation Information
 
-[More Information Needed]
+```bibtex
+@inproceedings{pudo23_interspeech,
+  author={Miko\l{}aj Pudo and Mateusz Wosik and Adam Cie\'slak and Justyna Krzywdziak and Bo\.{z}ena \L{}ukasiak and Artur Janicki},
+  title={{MOCKS} 1.0: Multilingual Open Custom Keyword Spotting Testset},
+  year={in press.},
+  booktitle={Proc. Interspeech 2023},
+}
+```
 
 ### Contributions