Update README.md

README.md

@@ -1,36 +1,65 @@
----
-license: apache-2.0
-dataset_info:
-  features:
-  - name: audio
-    dtype: audio
-  - name: transcript_annotated
-    dtype: string
-  - name: transcript_a
-    dtype: string
-  - name: transcript_b
-    dtype: string
-  - name: transcript_c
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 1343263191.5
-    num_examples: 4500
-  - name: validation
-    num_bytes: 75479207.0
-    num_examples: 250
-  - name: test
-    num_bytes: 72139425.0
-    num_examples: 250
-  download_size: 1482840572
-  dataset_size: 1490881823.5
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: validation
-    path: data/validation-*
-  - split: test
-    path: data/test-*
----
+---
+license: apache-2.0
+dataset_info:
+  features:
+  - name: audio
+    dtype: audio
+  - name: transcript_annotated
+    dtype: string
+  - name: transcript_a
+    dtype: string
+  - name: transcript_b
+    dtype: string
+  - name: transcript_c
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 1343263191.5
+    num_examples: 4500
+  - name: validation
+    num_bytes: 75479207.0
+    num_examples: 250
+  - name: test
+    num_bytes: 72139425.0
+    num_examples: 250
+  download_size: 1482840572
+  dataset_size: 1490881823.5
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: validation
+    path: data/validation-*
+  - split: test
+    path: data/test-*
+---
+
+# DisfluencySpeech Dataset
+
+The DisfluencySpeech Dataset is a single-speaker studio-quality labeled English speech dataset with paralanguage. 
+A single speaker recreates nearly 10 hours of expressive utterances from the Switchboard-1 Telephone Speech Corpus 
+(Switchboard), simulating realistic informal conversations. To aid the development of a text-to-speech (TTS) model that is able to 
+predictively synthesise paralanguage from text without such components, we provide three different transcripts at 
+different levels of information removal (removal of non-speech events, removal of non-sentence elements, 
+and removal of false starts).
+
+Benchmark TTS models for each transcript can be found here.
+
+# Dataset Details
+
+All audio files are provided as 22,050 hz _.wav_ files. In the _metadata.csv_ file, 4 different transcripts for each file are provided, 
+each at differing levels of information removal:
+
+- _transcript_annotated_ is a full transcript retaining all non-speech event and disfluency annotations;
+- _transcript_a_ contains all textual content recorded, including non-sentence elements and restarts.
+- Only non-speech events such as laughter and sighs are removed from transcript;
+- _transcript_b_ is _transcript_a_ but with filled pauses, explicit editing terms, and discourse markers removed.
+- Coordinating conjunctions and asides are left in, as they are non-sentence elements as well, they are often used to convey meaning; and
+- _transcript_c_ is _transcript_b_ but with false starts removed. This is the most minimal transcript.
+
+The training set contains 90% of the data, the validation set contains 5% of the data, and the test set contains 5% of the data.
+
+# Citation
+
+If you use this dataset, please cite the paper in which it is presented: _Kyra Wang, Dorien Herremans, 2024, DisfluencySpeech - Single-Speaker Conversational Speech Dataset with Paralanguage._