Update READMEs

datasets/air/README.md

@@ -3,18 +3,7 @@
 This project holds code
 to convert the Aachen Impulse Response ([air]) dataset
 to [audformat]
-and publish it with [audb]
-to a public Artifactory repository
-on https://audeering.jfrog.io.
-
-The databases is published under MIT
-and can be downloaded with the Python library [audb]:
-
-```python
-import audb
-
-db = audb.load('air')
-```
+and publish it with [audb].
 
 [air]: https://www.iks.rwth-aachen.de/en/research/tools-downloads/databases/aachen-impulse-response-database/
 [audb]: https://github.com/audeering/audb/

datasets/clac/README.md

@@ -1,6 +1,6 @@
-# CLAC
+# clac
 
-Publishes the Crowdsourced Language Assessment Corpus (CLAC) on Artifactory.
+Publishes the Crowdsourced Language Assessment Corpus (CLAC).
 
 The creation of the database is described in the
 following [paper](https://www.isca-speech.org/archive/pdfs/interspeech_2021/haulcy21_interspeech.pdf).

datasets/cmu-mosei/README.md

@@ -1,4 +1,4 @@
-# CMU-MOSEI
+# cmu-mosei
 
 Publishes `cmu-mosei` database, see
 https://github.com/A2Zadeh/CMU-MultimodalSDK

datasets/cmu-mosi/README.md

@@ -1,4 +1,4 @@
-# CMU-MOSI
+# cmu-mosi
 
 Publishes `cmu-mosi` database, see
 https://arxiv.org/abs/1606.06259

datasets/cochlscene/README.md

@@ -3,8 +3,7 @@
 Converts the [CochlScene]
 Dataset for Acoustic Scene Detection
 to [audformat]
-and publishes it with [audb]
-to Artifactory.
+and publishes it with [audb].
 
 [CochlScene]: https://zenodo.org/record/7080122
 [audformat]: https://github.com/audeering/audformat

datasets/cough-speech-sneeze/README.md

@@ -4,9 +4,7 @@ This project holds code
 to convert the [cough-speech-sneeze] corpus
 containing coughing, sneezing, speech, and silence
 to [audformat]
-and publish it with [audb]
-to a public Artifactory repository
-on https://audeering.jfrog.io.
+and publish it with [audb].
 
 The databases is published under [CC BY 4.0]
 and can be downloaded with the Python library [audb]:

datasets/crema-d/README.md

@@ -3,9 +3,7 @@
 This project holds code
 to convert the [crema-d] corpus
 to [audformat]
-and publish it with [audb]
-to a public Artifactory repository
-on https://audeering.jfrog.io.
+and publish it with [audb].
 
 The databases is published under [ODbL 1.0]
 and can be downloaded with the Python library [audb]:

datasets/eesc/README.md

@@ -1,6 +1,6 @@
 # eesc
 
-Publishes `eesc` on artifactory.
+Publishes the `eesc` dataset.
 
 For version `1.0.0`, the files in [1.0.0/sentence_reports_emotion](1.0.0/sentence_reports_emotion) were downloaded from
 http://peeter.eki.ee:5000/reports/segments by selecting each individual emotion, selecting `content influences` or

datasets/emodb/README.md

@@ -3,9 +3,7 @@
 This project holds code
 to convert the [emodb] database of acted emotions
 to [audformat]
-and published it with [audb]
-to a public Artifactory
-repository on https://audeering.jfrog.io.
+and published it with [audb].
 
 The databases is published under the [CC0-1.0] license
 and can be downloaded with the Python library [audb] by:

datasets/emouerj/README.md

@@ -1,3 +1,4 @@
-This project publishes the emoUERJ database is an emotional speech database in Portuguese. 
+# emouerj
 
-It contains 377 audios, which are variations of ten sentences pronounced in 4 different emotions (happiness, anger, sadness or neutral). The audios were recorded by eight speakers (4 mae, 4 female).
+Publishes the `emouerj`,
+an emotional speech dataset in Portuguese. 

datasets/emozionalmente/README.md

@@ -1,3 +1,3 @@
 # Emozionalmente
 
-Publishes `emozionalmente` on Artifactory.
+Publishes `emozionalmente`.

datasets/esc-50/README.md

@@ -3,8 +3,7 @@
 Converts the [ESC-50]
 Dataset for Environmental Sound Classification
 to [audformat]
-and publishes it with [audb]
-to Artifactory.
+and publishes it with [audb].
 
 [ESC-50]: https://github.com/karolpiczak/ESC-50
 [audformat]: https://github.com/audeering/audformat

datasets/fsdnoisy18k/README.md

@@ -3,8 +3,7 @@
 Converts the [FSDnoisy18k]
 Dataset for Sound Event Classification
 to [audformat]
-and publishes it with [audb]
-to Artifactory.
+and publishes it with [audb].
 
 [FSDnoisy18k]: http://www.eduardofonseca.net/FSDnoisy18k/
 [audformat]: https://github.com/audeering/audformat

datasets/ir-c4dm/README.md

@@ -1,2 +1,3 @@
 # ir-cm4d
 
+Publishes `ir-cm4d`.

datasets/kannada/README.md

@@ -1,2 +1,3 @@
-This project publishes the Kannada emotional speech dataset. This dataset contains six different sentences, pronounced by thirteen people (four male and nine female) in six emotions (anger, sadness, surprise, happiness, fear, neutral).
+# kannada
 
+Publishes `kannada` emotional dataset.

datasets/mesd/README.md

@@ -1,5 +1,3 @@
-# MESD
+# mesd
 
-Publishes MESD on Artifactory.
-
-MESD (Mexican Emotional Speech Database) contains single-word utterances for different emotions like anger, disgust, fear, happiness, neutral, and sadness
+Publishes `mesd` (Mexican Emotional Speech Database).

datasets/micirp/README.md

@@ -3,9 +3,7 @@
 This project holds code
 to convert the [micirp] dataset of microphone impulse responses
 to [audformat]
-and publish it with [audb]
-to a public Artifactory repository
-on https://audeering.jfrog.io.
+and publish it with [audb].
 
 The databases is published under [CC BY SA 4.0]
 and can be downloaded with the Python library [audb]:

datasets/musan/README.md

@@ -3,9 +3,7 @@
 This project holds code
 to convert the [musan] corpus of music, speech, and noise
 to [audformat]
-and publish it with [audb]
-to a public Artifactory repository
-on https://audeering.jfrog.io.
+and publish it with [audb].
 
 The databases is published under [CC BY 4.0]
 and can be downloaded with the Python library [audb]:

datasets/nemo/README.md

@@ -1,7 +1,4 @@
-This project publishes nEMO, which is a polish dataset. It contains over 3 hours of emotional speech in 6 categories: anger, fear, happiness, sadness, surprise and neutral. The audios were created by nine speakers
+# nemo
 
-Please install the requirements in the version folder:
-
-    virtualenv --python="python3.10" .venv
-    source .venv/bin/activate
-    pip install -r requirements.txt.lock
+Publishes `nemo`,
+a Polish emotional dataset.

datasets/openair/README.md

@@ -1,3 +1,3 @@
 # openair
 
-https://www.openair.hosted.york.ac.uk/?page_id=36
+Publishes [openair](https://www.openair.hosted.york.ac.uk/?page_id=36).

datasets/quechua/README.md

@@ -1,3 +1,5 @@
 # quechua
 
-Publish the `quechua` dataset from [figshare](https://figshare.com/articles/media/Quechua_Collao_for_Speech_Emotion_Recognition/20292516?file=37361143), see the [related paper](https://doi.org/10.1038/s41597-022-01855-9).
+Publish the `quechua` dataset from
+[figshare](https://figshare.com/articles/media/Quechua_Collao_for_Speech_Emotion_Recognition/20292516?file=37361143),
+see the [related paper](https://doi.org/10.1038/s41597-022-01855-9).

datasets/ravdess-videos/README.md

@@ -1,4 +1,4 @@
 # ravdess-videos
 
-Publish ravdess-videos database,
+Publish `ravdess-videos` dataset,
 see https://doi.org/10.5281/zenodo.1188976

datasets/ravdess/README.md

@@ -1,4 +1,3 @@
 # ravdess
 
-Publishes `ravdess` on Artifactory.
-
+Publishes `ravdess` (only audio files).

datasets/speech-accent-archive/README.md

@@ -1,8 +1,4 @@
-# Speech Accent Archive
+# speech-accent-archive
 
-The data is publised at https://www.kaggle.com/rtatman/speech-accent-archive
-and has been gathered from http://accent.gmu.edu.
-
-It includes 2140 speech samples, each from a different talker reading the same
-reading passage. Talkers come from 177 countries and have 214 different native
-languages. Each talker is speaking in English.
+Publish [speech-accent-archive](https://www.kaggle.com/rtatman/speech-accent-archive).
+It has been gathered from http://accent.gmu.edu.

datasets/subesco/README.md

@@ -1,5 +1,3 @@
-# SUBESCO
+# subesco
 
-Publishes SUBESCO on Artifactory.
-
-SUBESCO is an audio-only emotional speech corpus of 7000 sentence-level utterances of the Bangla language. The corpus contains 7:40:40h of audio and was evaluated by 50 raters. The emotions are Anger, Disgust, Fear, Happiness, Neutral, Sadness and Surprise.
+Publishes `subesco` emotional dataset in Bangla.

datasets/urbansound8k/README.md

@@ -3,8 +3,7 @@
 Converts the [urbansound8k]
 Dataset for Sound Event Classification
 to [audformat]
-and publishes it with [audb]
-to Artifactory.
+and publishes it with [audb].
 
 [urbansound8k]: https://urbansounddataset.weebly.com/
 [audformat]: https://github.com/audeering/audformat

datasets/vadtoolkit/README.md

@@ -3,9 +3,7 @@
 This project holds code
 to convert the [vadtoolkit] corpus
 to [audformat]
-and publish it with [audb]
-to a public Artifactory repository
-on https://audeering.jfrog.io.
+and publish it with [audb].
 
 The databases can be downloaded with the Python library [audb]:
 

datasets/wham/README.md

@@ -1,4 +1,4 @@
 # wham
 
 Publishes the WHAM! noise dataset from
-https://wham.whisper.ai
+https://wham.whisper.ai.