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Diffstat (limited to 'client/stt.py')
| -rw-r--r-- | client/stt.py | 155 |
1 files changed, 155 insertions, 0 deletions
diff --git a/client/stt.py b/client/stt.py new file mode 100644 index 0000000..3b3b81d --- /dev/null +++ b/client/stt.py @@ -0,0 +1,155 @@ +import os +import traceback +import json +import urllib2 + +""" +The default Speech-To-Text implementation which relies on PocketSphinx. +""" +class PocketSphinxSTT(object): + + def __init__(self, lmd = "languagemodel.lm", dictd = "dictionary.dic", + lmd_persona = "languagemodel_persona.lm", dictd_persona = "dictionary_persona.dic", + lmd_music=None, dictd_music=None): + """ + Initiates the pocketsphinx instance. + + Arguments: + speaker -- handles platform-independent audio output + lmd -- filename of the full language model + dictd -- filename of the full dictionary (.dic) + lmd_persona -- filename of the 'Persona' language model (containing, e.g., 'Jasper') + dictd_persona -- filename of the 'Persona' dictionary (.dic) + """ + + # quirky bug where first import doesn't work + try: + import pocketsphinx as ps + except: + import pocketsphinx as ps + + hmdir = "/usr/local/share/pocketsphinx/model/hmm/en_US/hub4wsj_sc_8k" + + if lmd_music and dictd_music: + self.speechRec_music = ps.Decoder(hmm = hmdir, lm = lmd_music, dict = dictd_music) + self.speechRec_persona = ps.Decoder( + hmm=hmdir, lm=lmd_persona, dict=dictd_persona) + self.speechRec = ps.Decoder(hmm=hmdir, lm=lmd, dict=dictd) + + def transcribe(self, audio_file_path, PERSONA_ONLY=False, MUSIC=False): + """ + Performs STT, transcribing an audio file and returning the result. + + Arguments: + audio_file_path -- the path to the audio file to-be transcribed + PERSONA_ONLY -- if True, uses the 'Persona' language model and dictionary + MUSIC -- if True, uses the 'Music' language model and dictionary + """ + + wavFile = file(audio_file_path, 'rb') + wavFile.seek(44) + + if MUSIC: + self.speechRec_music.decode_raw(wavFile) + result = self.speechRec_music.get_hyp() + elif PERSONA_ONLY: + self.speechRec_persona.decode_raw(wavFile) + result = self.speechRec_persona.get_hyp() + else: + self.speechRec.decode_raw(wavFile) + result = self.speechRec.get_hyp() + + print "===================" + print "JASPER: " + result[0] + print "===================" + + return result[0] + +""" +Speech-To-Text implementation which relies on the Google Speech API. + +This implementation requires a Google API key to be present in profile.yml + +To obtain an API key: +1. Join the Chromium Dev group: https://groups.google.com/a/chromium.org/forum/?fromgroups#!forum/chromium-dev +2. Create a project through the Google Developers console: https://console.developers.google.com/project +3. Select your project. In the sidebar, navigate to "APIs & Auth." Activate the Speech API. +4. Under "APIs & Auth," navigate to "Credentials." Create a new key for public API access. +5. Copy your API key and run client/populate.py. When prompted, paste this key for access to the Speech API. + +This implementation also requires that the avconv audio utility be present on your $PATH. On RPi, simply run: + sudo apt-get install avconv +""" +class GoogleSTT(object): + + RATE = 44100 + + def __init__(self, api_key): + """ + Arguments: + api_key - the public api key which allows access to Google APIs + """ + + self.api_key = api_key + for tool in ("avconv", "ffmpeg"): + if os.system("which %s" % tool) == 0: + self.audio_tool = tool + break + if not self.audio_tool: + raise Exception("Could not find an audio tool to convert .wav files to .flac") + + def transcribe(self, audio_file_path): + """ + Performs STT via the Google Speech API, transcribing an audio file + and returning an English string. + audio_file_path -- the path to the audio file to-be transcribed + + """ + AUDIO_FILE_FLAC = "active.flac" + os.system("%s -y -i %s -f flac -b:a 44100 %s" % (self.audio_tool, audio_file_path, AUDIO_FILE_FLAC)) + + url = "https://www.google.com/speech-api/v2/recognize?output=json&client=chromium&key=%s&lang=%s&maxresults=6&pfilter=2" % (self.api_key, "en-us") + flac = open(AUDIO_FILE_FLAC, 'rb') + data = flac.read() + flac.close() + try: + req = urllib2.Request( + url, + data=data, + headers={ + 'Content-type': 'audio/x-flac; rate=%s' % GoogleSTT.RATE}) + response_url = urllib2.urlopen(req) + response_read = response_url.read() + response_read = response_read.decode('utf-8') + decoded = json.loads(response_read.split("\n")[1]) + print response_read + text = decoded['result'][0]['alternative'][0]['transcript'] + if text: + print "===================" + print "JASPER: " + text + print "===================" + return text + except Exception: + traceback.print_exc() + +""" +Returns a Speech-To-Text engine. + +If api_key is not supplied, Jasper will rely on the PocketSphinx STT engine for +audio transcription. + +If api_key is supplied, Jasper will use the Google Speech API for transcribing +audio while in the active listen phase. Jasper will continue to rely on the +PocketSphinx engine during the passive listen phase, as the Google Speech API +is rate limited to 50 requests/day. + +Arguments: +api_key - if supplied, Jasper will use the Google Speech API for transcribing +audio in the active listen phase. + +""" +def newSTTEngine(api_key = None): + if api_key: + return GoogleSTT(api_key) + else: + return PocketSphinxSTT() |