nltk.corpus.reader.timit module

Read tokens, phonemes and audio data from the NLTK TIMIT Corpus.

This corpus contains selected portion of the TIMIT corpus.

  • 16 speakers from 8 dialect regions

  • 1 male and 1 female from each dialect region

  • total 130 sentences (10 sentences per speaker. Note that some sentences are shared among other speakers, especially sa1 and sa2 are spoken by all speakers.)

  • total 160 recording of sentences (10 recordings per speaker)

  • audio format: NIST Sphere, single channel, 16kHz sampling, 16 bit sample, PCM encoding

Module contents

The timit corpus reader provides 4 functions and 4 data items.

  • utterances

    List of utterances in the corpus. There are total 160 utterances, each of which corresponds to a unique utterance of a speaker. Here’s an example of an utterance identifier in the list:

    dr1-fvmh0/sx206
  - _----  _---
  | |  |   | |
  | |  |   | |
  | |  |   | `--- sentence number
  | |  |   `----- sentence type (a:all, i:shared, x:exclusive)
  | |  `--------- speaker ID
  | `------------ sex (m:male, f:female)
  `-------------- dialect region (1..8)

  • speakers

    List of speaker IDs. An example of speaker ID:

    dr1-fvmh0

    Note that if you split an item ID with colon and take the first element of the result, you will get a speaker ID.

    >>> itemid = 'dr1-fvmh0/sx206'
>>> spkrid , sentid = itemid.split('/')
>>> spkrid
'dr1-fvmh0'

    The second element of the result is a sentence ID.

  • dictionary()

    Phonetic dictionary of words contained in this corpus. This is a Python dictionary from words to phoneme lists.

  • spkrinfo()

    Speaker information table. It’s a Python dictionary from speaker IDs to records of 10 fields. Speaker IDs the same as the ones in timie.speakers. Each record is a dictionary from field names to values, and the fields are as follows:

    id         speaker ID as defined in the original TIMIT speaker info table
sex        speaker gender (M:male, F:female)
dr         speaker dialect region (1:new england, 2:northern,
           3:north midland, 4:south midland, 5:southern, 6:new york city,
           7:western, 8:army brat (moved around))
use        corpus type (TRN:training, TST:test)
           in this sample corpus only TRN is available
recdate    recording date
birthdate  speaker birth date
ht         speaker height
race       speaker race (WHT:white, BLK:black, AMR:american indian,
           SPN:spanish-american, ORN:oriental,???:unknown)
edu        speaker education level (HS:high school, AS:associate degree,
           BS:bachelor's degree (BS or BA), MS:master's degree (MS or MA),
           PHD:doctorate degree (PhD,JD,MD), ??:unknown)
comments   comments by the recorder

The 4 functions are as follows.

  • tokenized(sentences=items, offset=False)

    Given a list of items, returns an iterator of a list of word lists, each of which corresponds to an item (sentence). If offset is set to True, each element of the word list is a tuple of word(string), start offset and end offset, where offset is represented as a number of 16kHz samples.

  • phonetic(sentences=items, offset=False)

    Given a list of items, returns an iterator of a list of phoneme lists, each of which corresponds to an item (sentence). If offset is set to True, each element of the phoneme list is a tuple of word(string), start offset and end offset, where offset is represented as a number of 16kHz samples.

  • audiodata(item, start=0, end=None)

    Given an item, returns a chunk of audio samples formatted into a string. When the function is called, if start and end are omitted, the entire samples of the recording will be returned. If only end is omitted, samples from the start offset to the end of the recording will be returned.

  • play(data)

    Play the given audio samples. The audio samples can be obtained from the timit.audiodata function.

class nltk.corpus.reader.timit.SpeakerInfo[source]

Bases: object

__init__(id, sex, dr, use, recdate, birthdate, ht, race, edu, comments=None)[source]
class nltk.corpus.reader.timit.TimitCorpusReader[source]

Bases: CorpusReader

Reader for the TIMIT corpus (or any other corpus with the same file layout and use of file formats). The corpus root directory should contain the following files:

  • timitdic.txt: dictionary of standard transcriptions

  • spkrinfo.txt: table of speaker information

In addition, the root directory should contain one subdirectory for each speaker, containing three files for each utterance:

  • <utterance-id>.txt: text content of utterances

  • <utterance-id>.wrd: tokenized text content of utterances

  • <utterance-id>.phn: phonetic transcription of utterances

  • <utterance-id>.wav: utterance sound file

__init__(root, encoding='utf8')[source]

Construct a new TIMIT corpus reader in the given directory. :param root: The root directory for this corpus.

audiodata(utterance, start=0, end=None)[source]
fileids(filetype=None)[source]

Return a list of file identifiers for the files that make up this corpus.

Parameters

filetype – If specified, then filetype indicates that only the files that have the given type should be returned. Accepted values are: txt, wrd, phn, wav, or metadata,

phone_times(utterances=None)[source]

offset is represented as a number of 16kHz samples!

phone_trees(utterances=None)[source]
phones(utterances=None)[source]
play(utterance, start=0, end=None)[source]

Play the given audio sample.

Parameters

utterance – The utterance id of the sample to play

sent_times(utterances=None)[source]
sentid(utterance)[source]
sents(utterances=None)[source]
spkrid(utterance)[source]
spkrinfo(speaker)[source]
Returns

A dictionary mapping .. something.

spkrutteranceids(speaker)[source]
Returns

A list of all utterances associated with a given speaker.

transcription_dict()[source]
Returns

A dictionary giving the ‘standard’ transcription for each word.

utterance(spkrid, sentid)[source]
utteranceids(dialect=None, sex=None, spkrid=None, sent_type=None, sentid=None)[source]
Returns

A list of the utterance identifiers for all utterances in this corpus, or for the given speaker, dialect region, gender, sentence type, or sentence number, if specified.

wav(utterance, start=0, end=None)[source]
word_times(utterances=None)[source]
words(utterances=None)[source]
nltk.corpus.reader.timit.read_timit_block(stream)[source]

Block reader for timit tagged sentences, which are preceded by a sentence number that will be ignored.