Merge pull request #118 from astahlman/master

LGTM! Thanks for the fine work and revisions.

1 files changed, 153 insertions, 0 deletions

diff --git a/client/stt.py b/client/stt.py
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+++ b/client/stt.py
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+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, **kwargs):
+        """
+            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. Add your credentials to your profile.yml. Add an entry to the 'keys' section using the key name 'GOOGLE_SPEECH.' Sample configuration:
+6. Set the value of the 'stt_engine' key in your profile.yml to 'google'
+
+
+Excerpt from sample profile.yml:
+
+    ...
+    timezone: US/Pacific
+    stt_engine: google
+    keys:
+        GOOGLE_SPEECH: $YOUR_KEY_HERE
+
+"""
+class GoogleSTT(object):
+
+    RATE = 16000
+
+    def __init__(self, api_key, **kwargs):
+        """
+        Arguments:
+        api_key - the public api key which allows access to Google APIs
+        """
+        self.api_key = api_key
+
+    def transcribe(self, audio_file_path, PERSONA_ONLY=False, MUSIC=False):
+        """
+            Performs STT via the Google Speech API, transcribing an audio file 
+            and returning an English string.
+
+            Arguments:
+                audio_file_path -- the path to the .wav file to be transcribed
+        """
+        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")
+
+        wav = open(audio_file_path, 'rb')
+        data = wav.read()
+        wav.close()
+
+        try:
+            req = urllib2.Request(
+                url,
+                data=data,
+                headers={
+                    'Content-type': 'audio/l16; 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.
+
+Currently, the supported implementations are the default Pocket Sphinx and
+the Google Speech API
+
+Arguments:
+    engine_type - one of "sphinx" or "google"
+    kwargs - keyword arguments passed to the constructor of the STT engine
+"""
+def newSTTEngine(engine_type, **kwargs):
+    t = engine_type.lower()
+    if t == "sphinx":
+        return PocketSphinxSTT(**kwargs)
+    elif t == "google":
+        return GoogleSTT(**kwargs)
+    else:
+        raise ValueError("Unsupported STT engine type: " + engine_type)