Coverage for nltk.corpus.reader.timit : 25%
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# Natural Language Toolkit: TIMIT Corpus Reader # # Copyright (C) 2001-2007 NLTK Project # Author: Haejoong Lee <haejoong@ldc.upenn.edu> # Steven Bird <sb@ldc.upenn.edu> # Jacob Perkins <japerk@gmail.com> # URL: <http://www.nltk.org/> # For license information, see LICENSE.TXT
# [xx] this docstring is out-of-date: Read tokens, phonemes and audio data from the NLTK TIMIT Corpus.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 fuction 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.
"""
""" 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 """
r'timitdic\.txt|spkrinfo\.txt') """A regexp matching fileids that are used by this corpus reader."""
""" Construct a new TIMIT corpus reader in the given directory. :param root: The root directory for this corpus. """ # Ensure that wave files don't get treated as unicode data: encoding = [('.*\.wav', None), ('.*', encoding)]
find_corpus_fileids(root, self._FILE_RE), encoding=encoding)
find_corpus_fileids(root, self._UTTERANCE_RE)] """A list of the utterance identifiers for all utterances in this corpus."""
""" Return a list of file identifiers for the files that make up this corpus.
:param 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``, """ if filetype is None: return CorpusReader.fileids(self) elif filetype in ('txt', 'wrd', 'phn', 'wav'): return ['%s.%s' % (u, filetype) for u in self._utterances] elif filetype == 'metadata': return ['timitdic.txt', 'spkrinfo.txt'] else: raise ValueError('Bad value for filetype: %r' % filetype)
sent_type=None, sentid=None): """ :return: 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. """ if isinstance(dialect, compat.string_types): dialect = [dialect] if isinstance(sex, compat.string_types): sex = [sex] if isinstance(spkrid, compat.string_types): spkrid = [spkrid] if isinstance(sent_type, compat.string_types): sent_type = [sent_type] if isinstance(sentid, compat.string_types): sentid = [sentid]
utterances = self._utterances[:] if dialect is not None: utterances = [u for u in utterances if u[2] in dialect] if sex is not None: utterances = [u for u in utterances if u[4] in sex] if spkrid is not None: utterances = [u for u in utterances if u[:9] in spkrid] if sent_type is not None: utterances = [u for u in utterances if u[11] in sent_type] if sentid is not None: utterances = [u for u in utterances if u[10:] in spkrid] return utterances
""" :return: A dictionary giving the 'standard' transcription for each word. """ _transcriptions = {} for line in self.open('timitdic.txt'): if not line.strip() or line[0] == ';': continue m = re.match(r'\s*(\S+)\s+/(.*)/\s*$', line) if not m: raise ValueError('Bad line: %r' % line) _transcriptions[m.group(1)] = m.group(2).split() return _transcriptions
return utterance.split('/')[0]
return utterance.split('/')[1]
return '%s/%s' % (spkrid, sentid)
""" :return: A list of all utterances associated with a given speaker. """ return [utterance for utterance in self._utterances if utterance.startswith(speaker+'/')]
""" :return: A dictionary mapping .. something. """ if speaker in self._utterances: speaker = self.spkrid(speaker)
if self._speakerinfo is None: self._speakerinfo = {} for line in self.open('spkrinfo.txt'): if not line.strip() or line[0] == ';': continue rec = line.strip().split(None, 9) key = "dr%s-%s%s" % (rec[2],rec[1].lower(),rec[0].lower()) self._speakerinfo[key] = SpeakerInfo(*rec)
return self._speakerinfo[speaker]
return [line.split()[-1] for fileid in self._utterance_fileids(utterances, '.phn') for line in self.open(fileid) if line.strip()]
""" offset is represented as a number of 16kHz samples! """ return [(line.split()[2], int(line.split()[0]), int(line.split()[1])) for fileid in self._utterance_fileids(utterances, '.phn') for line in self.open(fileid) if line.strip()]
return [line.split()[-1] for fileid in self._utterance_fileids(utterances, '.wrd') for line in self.open(fileid) if line.strip()]
return [(line.split()[2], int(line.split()[0]), int(line.split()[1])) for fileid in self._utterance_fileids(utterances, '.wrd') for line in self.open(fileid) if line.strip()]
return [[line.split()[-1] for line in self.open(fileid) if line.strip()] for fileid in self._utterance_fileids(utterances, '.wrd')]
return [(line.split(None,2)[-1].strip(), int(line.split()[0]), int(line.split()[1])) for fileid in self._utterance_fileids(utterances, '.txt') for line in self.open(fileid) if line.strip()]
if utterances is None: utterances = self._utterances if isinstance(utterances, compat.string_types): utterances = [utterances]
trees = [] for utterance in utterances: word_times = self.word_times(utterance) phone_times = self.phone_times(utterance) sent_times = self.sent_times(utterance)
while sent_times: (sent, sent_start, sent_end) = sent_times.pop(0) trees.append(Tree('S', [])) while (word_times and phone_times and phone_times[0][2] <= word_times[0][1]): trees[-1].append(phone_times.pop(0)[0]) while word_times and word_times[0][2] <= sent_end: (word, word_start, word_end) = word_times.pop(0) trees[-1].append(Tree(word, [])) while phone_times and phone_times[0][2] <= word_end: trees[-1][-1].append(phone_times.pop(0)[0]) while phone_times and phone_times[0][2] <= sent_end: trees[-1].append(phone_times.pop(0)[0]) return trees
# [xx] NOTE: This is currently broken -- we're assuming that the # fileids are WAV fileids (aka RIFF), but they're actually NIST SPHERE # fileids. # nltk.chunk conflicts with the stdlib module 'chunk' wave = import_from_stdlib('wave')
w = wave.open(self.open(utterance+'.wav'), 'rb')
if end is None: end = w.getnframes()
# Skip past frames before start, then read the frames we want w.readframes(start) frames = w.readframes(end-start)
# Open a new temporary file -- the wave module requires # an actual file, and won't work w/ stringio. :( tf = tempfile.TemporaryFile() out = wave.open(tf, 'w')
# Write the parameters & data to the new file. out.setparams(w.getparams()) out.writeframes(frames) out.close()
# Read the data back from the file, and return it. The # file will automatically be deleted when we return. tf.seek(0) return tf.read()
assert(end is None or end > start) headersize = 44 if end is None: data = self.open(utterance+'.wav').read() else: data = self.open(utterance+'.wav').read(headersize+end*2) return data[headersize+start*2:]
if utterances is None: utterances = self._utterances if isinstance(utterances, compat.string_types): utterances = [utterances] return ['%s%s' % (u, extension) for u in utterances]
""" Play the given audio sample.
:param utterance: The utterance id of the sample to play """ # Method 1: os audio dev. try: import ossaudiodev try: dsp = ossaudiodev.open('w') dsp.setfmt(ossaudiodev.AFMT_S16_LE) dsp.channels(1) dsp.speed(16000) dsp.write(self.audiodata(utterance, start, end)) dsp.close() except IOError as e: print(("can't acquire the audio device; please " "activate your audio device."), file=sys.stderr) print("system error message:", str(e), file=sys.stderr) return except ImportError: pass
# Method 2: pygame try: # FIXME: this won't work under python 3 import pygame.mixer, StringIO pygame.mixer.init(16000) f = StringIO.StringIO(self.wav(utterance, start, end)) pygame.mixer.Sound(f).play() while pygame.mixer.get_busy(): time.sleep(0.01) return except ImportError: pass
# Method 3: complain. :) print(("you must install pygame or ossaudiodev " "for audio playback."), file=sys.stderr)
ht, race, edu, comments=None): self.id = id self.sex = sex self.dr = dr self.use = use self.recdate = recdate self.birthdate = birthdate self.ht = ht self.race = race self.edu = edu self.comments = comments
attribs = 'id sex dr use recdate birthdate ht race edu comments' args = ['%s=%r' % (attr, getattr(self, attr)) for attr in attribs.split()] return 'SpeakerInfo(%s)' % (', '.join(args))
""" Block reader for timit tagged sentences, which are preceded by a sentence number that will be ignored. """ line = stream.readline() if not line: return [] n, sent = line.split(' ', 1) return [sent] |