Update files from the datasets library (from 1.15.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.15.0

README.md

@@ -60,6 +60,9 @@ languages:
   - kn
   SLR80:
   - my
+  SLR83:
+  - en-GB
+  - en-IE
   SLR86:
   - yo
 licenses:
@@ -494,6 +497,19 @@ https://github.com/google/language-resources#license for license information.
 
 Copyright 2018, 2019 Google, Inc.
 
+#### SLR83: Crowdsourced high-quality UK and Ireland English Dialect speech data set
+This data set contains transcribed high-quality audio of English sentences recorded by volunteers speaking different dialects of the language.
+The data set consists of wave files, and a TSV file (line_index.tsv). The file line_index.csv contains a line id, an anonymized FileID and the transcription of audio in the file.
+
+The data set has been manually quality checked, but there might still be errors.
+
+The recordings from the Welsh English speakers were collected in collaboration with Cardiff University.
+
+The dataset is distributed under Creative Commons Attribution-ShareAlike 4.0 International Public License.
+See [LICENSE](https://www.openslr.org/resources/83/LICENSE) file and https://github.com/google/language-resources#license for license information.
+
+Copyright 2018, 2019 Google, Inc.
+
 #### SLR86: Crowdsourced high-quality  multi-speaker speech data set
 This data set contains transcribed high-quality audio of  sentences recorded by volunteers. The data set 
 consists of wave files, and a TSV file (line_index.tsv). The file line_index.tsv contains a anonymized FileID and 
@@ -539,15 +555,48 @@ A typical data point comprises the path to the audio file, called path and its s
 
 ### Data Fields
 
-path: The path to the audio file
-
-audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`.
-
-sentence: The sentence the user was prompted to speak
+- `path`: The path to the audio file.
+- `audio`: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling
+  rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and
+  resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might
+  take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column,
+  *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`.
+- `sentence`: The sentence the user was prompted to speak.
 
 ### Data Splits
 
-The speech material has only train dataset.
+There is only one "train" split for all configurations and the number of examples are:
+
+|       |   Number of examples |
+|:------|---------------------:|
+| SLR41 |                 5822 |
+| SLR42 |                 2906 |
+| SLR43 |                 2064 |
+| SLR44 |                 4213 |
+| SLR63 |                 4126 |
+| SLR64 |                 1569 |
+| SLR65 |                 4284 |
+| SLR66 |                 4448 |
+| SLR69 |                 4240 |
+| SLR35 |               185076 |
+| SLR36 |               219156 |
+| SLR70 |                 3359 |
+| SLR71 |                 4374 |
+| SLR72 |                 4903 |
+| SLR73 |                 5447 |
+| SLR74 |                  617 |
+| SLR75 |                 3357 |
+| SLR76 |                 7136 |
+| SLR77 |                 5587 |
+| SLR78 |                 4272 |
+| SLR79 |                 4400 |
+| SLR80 |                 2530 |
+| SLR86 |                 3583 |
+| SLR32 |                 9821 |
+| SLR52 |               185293 |
+| SLR53 |               218703 |
+| SLR54 |               157905 |
+| SLR83 |                17877 |
 
 ## Dataset Creation
 

dummy/SLR83/0.0.0/dummy_data.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:03779b24ded8747ba803788c0cf632655827f3f5e59ba1ae189f132217610691
+size 7528

openslr.py

@@ -112,6 +112,20 @@ SLR71, SLR71, SLR72, SLR73, SLR74, SLR75:
     ISBN = {979-10-95546-34-4},
 }
 
+SLR83
+@inproceedings{demirsahin-etal-2020-open,
+    title = {{Open-source Multi-speaker Corpora of the English Accents in the British Isles}},
+    author = {Demirsahin, Isin and Kjartansson, Oddur and Gutkin, Alexander and Rivera, Clara},
+    booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference (LREC)},
+    month = may,
+    year = {2020},
+    pages = {6532--6541},
+    address = {Marseille, France},
+    publisher = {European Language Resources Association (ELRA)},
+    url = {https://www.aclweb.org/anthology/2020.lrec-1.804},
+    ISBN = {979-10-95546-34-4},
+}
+
 SLR80
 @inproceedings{oo-etal-2020-burmese,
     title = {{Burmese Speech Corpus, Finite-State Text Normalization and Pronunciation Grammars with an Application
@@ -479,6 +493,39 @@ _RESOURCES = {
         "IndexFiles": ["line_index.tsv"],
         "DataDirs": [""],
     },
+    "SLR83": {
+        "Language": "English",
+        "LongName": "Crowdsourced high-quality UK and Ireland English Dialect speech data set",
+        "Category": "Speech",
+        "Summary": "Data set which contains male and female recordings of English from various dialects of the UK and Ireland",
+        "Files": [
+            "irish_english_male.zip",
+            "midlands_english_female.zip",
+            "midlands_english_male.zip",
+            "northern_english_female.zip",
+            "northern_english_male.zip",
+            "scottish_english_female.zip",
+            "scottish_english_male.zip",
+            "southern_english_female.zip",
+            "southern_english_male.zip",
+            "welsh_english_female.zip",
+            "welsh_english_male.zip",
+        ],
+        "IndexFiles": [
+            "line_index.csv",
+            "line_index.csv",
+            "line_index.csv",
+            "line_index.csv",
+            "line_index.csv",
+            "line_index.csv",
+            "line_index.csv",
+            "line_index.csv",
+            "line_index.csv",
+            "line_index.csv",
+            "line_index.csv",
+        ],
+        "DataDirs": ["", "", "", "", "", "", "", "", "", "", ""],
+    },
     "SLR86": {
         "Language": "Yoruba",
         "LongName": "Crowdsourced high-quality Yoruba speech data set",
@@ -593,6 +640,16 @@ class OpenSlr(datasets.GeneratorBasedBuilder):
                     sentence = sentence_index[filename]
                     counter += 1
                     yield counter, {"path": path, "audio": path, "sentence": sentence}
+        elif self.config.name in ["SLR83"]:
+            for i, path_to_index in enumerate(path_to_indexs):
+                with open(path_to_index, encoding="utf-8") as f:
+                    lines = f.readlines()
+                    for id_, line in enumerate(lines):
+                        field_values = re.split(r",\s?", line.strip())
+                        user_id, filename, sentence = field_values
+                        path = os.path.join(path_to_datas[i], f"{filename}.wav")
+                        counter += 1
+                        yield counter, {"path": path, "audio": path, "sentence": sentence}
         else:
             for i, path_to_index in enumerate(path_to_indexs):
                 with open(path_to_index, encoding="utf-8") as f: