Polishing the language of README.md

README.md

@@ -71,13 +71,13 @@ Please refer to our [paper](https://www.isca-speech.org/archive/pdfs/interspeech
 
 ### Supported Tasks and Leaderboards
 
-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.
+The MOCKS dataset can be used for the Open-Vocabulary Keyword Spotting (OV-KWS) task. It supports two OV-KWS types:
+- Query-by-Text, where the keyword is provided by text and needs to be detected in the audio stream.
+- Query-by-Example, where the keyword is provided with enrollment audio for detection in the 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.
+- offline keyword detection, where test audio is trimmed to contain only keywords of interest.
+- online (streaming) keyword detection, where test audio has past and future context besides keywords of interest.
 
 ### Languages
 
@@ -90,7 +90,7 @@ The MOCKS incorporates 5 languages:
 
 ## Dataset Structure
 
-The MOCKS testset is split by language, source dataset and OV-KWS type:
+The MOCKS testset is split by language, source dataset, and OV-KWS type:
 ```
 MOCKS
 │
@@ -138,25 +138,25 @@ MOCKS
 ```
 
 Each split is divided into:
-- positive examples (`all.pair.positive.tsv`) - test examples with true keyword, 5000-8000 keywords in each subset,
-- similar examples (`all.pair.similar.tsv`) - test examples with similar phrases to keyword selected based on phonetic transcription distance,
-- different examples (`all.pair.different.tsv`) - test examples with completaly different prases.
+- positive examples (`all.pair.positive.tsv`) - test examples with true keywords, 5000-8000 keywords in each subset,
+- similar examples (`all.pair.similar.tsv`) - test examples with similar phrases to the keyword selected based on phonetic transcription distance,
+- different examples (`all.pair.different.tsv`) - test examples with completely different phrases.
 
 All those files contain columns separated by tab:
 - `keyword_path` - path to audio containing keyword phrase.
 - `adversary_keyword_path` - path to test audio.
-- `adversary_keyword_timestamp_start` - start time in seconds of phrase of interest for given keyword from `keyword_path`, field only available in **offline** split.
-- `adversary_keyword_timestamp_end` - end time in seconds of phrase of interest for given keyword from `keyword_path`, field only available in **offline** split.
+- `adversary_keyword_timestamp_start` - start time in seconds of phrase of interest for a given keyword from `keyword_path`, the field only available in **offline** split.
+- `adversary_keyword_timestamp_end` - end time in seconds of phrase of interest for a given keyword from `keyword_path`, the field only available in **offline** split.
 - `label` - whether the `adversary_keyword_path` contain keyword from `keyword_path` or not (1 - contains keyword, 0 - doesn't contain keyword).
 
-Each split also contains subset of whole data with the same field sctructure to allow faster evaluation (`subset.pair.*.tsv`).
+Each split also contains a subset of whole data with the same field structure to allow faster evaluation (`subset.pair.*.tsv`).
 
-Also, trascriptions are provided for each audio in:
+Also, transcriptions are provided for each audio in:
 - `data_offline_transcription.tsv` - transcriptions for **offline** examples and `keyword_path` from **online** scenario,
-- `data_online_transcription.tsv` - transcriptions for adversary, test examples from **online** scenario,
+- `data_online_transcription.tsv` - transcriptions for the adversary, test examples from **online** scenario,
 
 three columns are present within each file:
-- `path_to_keyword`/`path_to_adversary_keyword` - path to audio file,
+- `path_to_keyword`/`path_to_adversary_keyword` - path to the audio file,
 - `keyword_transcription`/`adversary_keyword_transcription` - audio transcription,
 - `keyword_phonetic_transcription`/`adversary_keyword_phonetic_transcription` - audio phonetic transcription.
 
@@ -166,8 +166,10 @@ The dataset can be used by:
 - downloading the archive and constructing all the test cases based on the provided `tsv` files,
 - `datasets` package.
 
-In the latter case the following should work:
-```load_dataset(path="voiceintelligenceresearch/MOCKS", name="en.LS-clean", split="offline")```
+In the latter case, the following should work:
+```
+load_dataset(path="voiceintelligenceresearch/MOCKS", name="en.LS-clean", split="offline")
+```
 
 The allowed values for `name` are:
 - `en.LS-{clean,other}`,
@@ -218,13 +220,13 @@ All the test files are provided in 16 kHz, even though `{de,en,es,fr,it}.MCV` fi
 
 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.
+- 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.
+The offline testset contains an additional 0.1 seconds at the beginning and end of the extracted audio sample to mitigate the cut-speech effect.
+The online version contains an additional 1 second or so at the beginning and end of the extracted audio sample.
 
 The MOCKS testset is gender balanced.