diff --git a/.vs/acoustic_model/v15/.suo b/.vs/acoustic_model/v15/.suo
index 586e8a9..e9ddb30 100644
Binary files a/.vs/acoustic_model/v15/.suo and b/.vs/acoustic_model/v15/.suo differ
diff --git a/acoustic_model/__pycache__/defaultfiles.cpython-36.pyc b/acoustic_model/__pycache__/defaultfiles.cpython-36.pyc
index b05a221..5792309 100644
Binary files a/acoustic_model/__pycache__/defaultfiles.cpython-36.pyc and b/acoustic_model/__pycache__/defaultfiles.cpython-36.pyc differ
diff --git a/acoustic_model/acoustic_model.pyproj b/acoustic_model/acoustic_model.pyproj
index 7a2f4b5..27625c9 100644
--- a/acoustic_model/acoustic_model.pyproj
+++ b/acoustic_model/acoustic_model.pyproj
@@ -4,7 +4,7 @@
2.0
4d8c8573-32f0-4a62-9e62-3ce5cc680390
.
- performance_check.py
+ check_novoapi.py
.
@@ -25,6 +25,7 @@
Code
+
Code
@@ -34,7 +35,7 @@
Code
-
+
Code
diff --git a/acoustic_model/check_novoapi.py b/acoustic_model/check_novoapi.py
index 35da212..93ec540 100644
--- a/acoustic_model/check_novoapi.py
+++ b/acoustic_model/check_novoapi.py
@@ -20,13 +20,8 @@ from forced_alignment import pyhtk
import novoapi
-## ======================= convert phones ======================
-mapping = convert_xsampa2ipa.load_converter('xsampa', 'ipa', default.ipa_xsampa_converter_dir)
-stimmen_transcription_ = pd.ExcelFile(default.stimmen_transcription_xlsx)
-
-
-## novo phoneset
+## ======================= novo phoneset ======================
translation_key = dict()
#phonelist_novo70_ = pd.ExcelFile(default.phonelist_novo70_xlsx)
@@ -54,3 +49,14 @@ with open(default.cmu69_phoneset, "rt", encoding="utf-8") as fin:
phoneset_ipa = np.unique(phoneset_ipa)
phoneset_novo70 = np.unique(phoneset_novo70)
+
+## ======================= convert phones ======================
+mapping = convert_xsampa2ipa.load_converter('xsampa', 'ipa', default.ipa_xsampa_converter_dir)
+
+stimmen_transcription_ = pd.ExcelFile(default.stimmen_transcription_xlsx)
+df = pd.read_excel(stimmen_transcription_, 'check')
+#for xsampa, ipa in zip(df['X-SAMPA'], df['IPA']):
+# #ipa_converted = convert_xsampa2ipa.conversion('xsampa', 'ipa', mapping, xsampa_)
+# ipa_converted = convert_xsampa2ipa.xsampa2ipa(mapping, xsampa)
+# if not ipa_converted == ipa:
+# print('{0}: {1} - {2}'.format(xsampa, ipa_converted, ipa))
\ No newline at end of file
diff --git a/acoustic_model/defaultfiles.py b/acoustic_model/defaultfiles.py
index 4f98e6c..726f23a 100644
--- a/acoustic_model/defaultfiles.py
+++ b/acoustic_model/defaultfiles.py
@@ -40,5 +40,6 @@ stimmen_transcription_xlsx = os.path.join(experiments_dir, 'stimmen', 'data', 'F
stimmen_data_dir = os.path.join(experiments_dir, 'stimmen', 'data')
phonelist_friesian_txt = os.path.join(experiments_dir, 'friesian', 'acoustic_model', 'config', 'phonelist_friesian.txt')
-novo_api_dir = os.path.join(WSL_dir, 'python-novo-api')
-cmu69_phoneset = os.path.join(novo_api_dir, 'novoapi', 'asr', 'phoneset', 'en', 'cmu69.phoneset')
\ No newline at end of file
+novo_api_dir = os.path.join(WSL_dir, 'python-novo-api', 'novoapi')
+#novo_api_dir = r'c:\Python36-32\Lib\site-packages\novoapi'
+cmu69_phoneset = os.path.join(novo_api_dir, 'asr', 'phoneset', 'en', 'cmu69.phoneset')
\ No newline at end of file
diff --git a/acoustic_model/performance_check.py b/acoustic_model/htk_vs_kaldi.py
similarity index 100%
rename from acoustic_model/performance_check.py
rename to acoustic_model/htk_vs_kaldi.py
diff --git a/novoapi/__init__.py b/novoapi/__init__.py
new file mode 100644
index 0000000..9ff2f76
--- /dev/null
+++ b/novoapi/__init__.py
@@ -0,0 +1,5 @@
+#!/usr/bin/env python
+
+__version__ = "0.2"
+
+import backend
diff --git a/novoapi/asr/__init__.py b/novoapi/asr/__init__.py
new file mode 100644
index 0000000..2832e82
--- /dev/null
+++ b/novoapi/asr/__init__.py
@@ -0,0 +1,6 @@
+#!/usr/bin/env python
+
+#import segments
+#import spraaklab
+from . import segments
+from . import spraaklab
\ No newline at end of file
diff --git a/novoapi/asr/segments/__init__.py b/novoapi/asr/segments/__init__.py
new file mode 100644
index 0000000..737e432
--- /dev/null
+++ b/novoapi/asr/segments/__init__.py
@@ -0,0 +1,4 @@
+#!/usr/bin/env python
+
+from .segments import Segmentation
+from .praat import seg2tg
diff --git a/novoapi/asr/segments/praat.py b/novoapi/asr/segments/praat.py
new file mode 100644
index 0000000..fbc9e4c
--- /dev/null
+++ b/novoapi/asr/segments/praat.py
@@ -0,0 +1,77 @@
+#!/usr/bin/env python
+# (c) 2015--2018 NovoLanguage, author: David A. van Leeuwen
+
+import codecs
+
+def print_header(output, begin, end, nr_tiers):
+ print >> output, 'File type = "ooTextFile"'
+ print >> output, 'Object class = "TextGrid"'
+ print >> output, ''
+ print >> output, 'xmin = %s' % begin
+ print >> output, 'xmax = %s' % end
+ print >> output, 'tiers? '
+ print >> output, 'size = %d' % nr_tiers
+ print >> output, 'item []:'
+
+
+def print_info_tier(output, title, begin, end, label):
+ print >> output, '\titem [%d]:' % 0
+ print >> output, '\t\tclass = "IntervalTier"'
+ print >> output, '\t\tname = "%s"' % title
+ print >> output, '\t\txmin = %s' % begin
+ print >> output, '\t\txmax = %s' % end
+ print >> output, '\t\tintervals: size = %d' % 1
+
+ print >> output, '\t\tintervals [1]:'
+ print >> output, '\t\t\txmin = %s' % begin
+ print >> output, '\t\t\txmax = %s' % end
+ print >> output, '\t\t\ttext = "%s"' % label
+
+
+#def print_tier(output, title, begin, end, segs, (format, formatter)):
+def print_tier(output, title, begin, end, segs, format, formatter):
+ print >> output, '\titem [%d]:' % 0
+ print >> output, '\t\tclass = "IntervalTier"'
+ print >> output, '\t\tname = "%s"' % title
+ print >> output, '\t\txmin = %s' % begin
+ print >> output, '\t\txmax = %s' % end
+ print >> output, '\t\tintervals: size = %d' % len(segs)
+
+ count = 1
+ for seg in segs:
+ #print seg
+ print >> output, '\t\tintervals [%d]:' % count
+ print >> output, '\t\t\txmin = %s' % repr(int(seg['begin']) / 100.0)
+ print >> output, '\t\t\txmax = %s' % repr(int(seg['end']) / 100.0)
+ string = '\t\t\ttext = "' + format + '"'
+ print >> output, string % formatter(seg['label'])
+ count += 1
+
+
+def seg2tg(fname, segments):
+ if not segments:
+ return
+ output = codecs.open(fname, "w", encoding="utf-8")
+
+ confidences = []
+ word_labels = []
+ phones = []
+
+ for s in segments:
+ conf = s.llh if hasattr(s, "llh") else s.score
+ confidences.append({'begin': s.begin, 'end': s.end, 'label': conf})
+ word_labels.append({'begin': s.begin, 'end': s.end, 'label': s.label})
+ for p in s.phones:
+ phones.append({'begin': p.begin, 'end': p.end, 'label': p.label})
+
+
+ begin = repr(int(segments[0].begin) / 100.0)
+ end = repr(int(segments[-1].end) / 100.0)
+
+ nr_tiers = 3
+ print_header(output, begin, end, nr_tiers)
+ print_tier(output, "confidence", begin, end, confidences, ('%.3f', lambda x: x))
+ print_tier(output, "words", begin, end, word_labels, ('%s', lambda x: x))
+ print_tier(output, "phones", begin, end, phones, ('%s', lambda x: x))
+
+ output.close()
diff --git a/novoapi/asr/segments/segments.py b/novoapi/asr/segments/segments.py
new file mode 100644
index 0000000..ee5dbcc
--- /dev/null
+++ b/novoapi/asr/segments/segments.py
@@ -0,0 +1,99 @@
+#!/usr/bin/env python
+# (c) 2015--2018 NovoLanguage, author: David A. van Leeuwen
+
+## These classes can be initialized with dictionaries, as they are returned by the python spraaklab recognition system.
+
+class Segment(object):
+ def __init__(self, segment):
+ self.begin = segment["begin"]
+ self.end = segment["end"]
+ self.begintime = segment.get("beginTime", self.begin / 100.0)
+ self.endtime = segment.get("endTime", self.end / 100.0)
+ self.label = segment["label"]
+ self.score = segment["score"]
+ if "llh" in segment:
+ self.llh = segment["llh"]
+ if "phones" in segment:
+ self.type = "word"
+ self.phones = Segmentation(segment["phones"], ["sil"])
+ if hasattr(self.phones[0], "llh"):
+ self.minllh = min([s.llh for s in self.phones]) ## the current word llh for error detection
+ else:
+ self.type = "phone"
+
+ def __repr__(self):
+ res = "%8.3f -- %8.3f score %8.3f " % (self.begintime, self.endtime, self.score)
+ if hasattr(self, "llh"):
+ res += "llh %8.3f " % self.llh
+ res += self.label.encode("utf8")
+ return res
+
+ def export(self):
+ r = {"begin": self.begin, "end": self.end, "label": self.label, "score": self.score, "type": self.type}
+ if hasattr(self, "llh"):
+ r["llh"] = self.llh
+ if hasattr(self, "phones"):
+ r["phones"] = self.phones.export()
+ return r
+
+class Segmentation(object):
+ def __init__(self, segments, sils=["", "", "!sil"]):
+ """Create a segmentation from a spraaklab recognition structure.
+ segments: an array of words (or phones), represented by a dict with
+ "begin", "end", "label", "score", and "llh" keys. Words can also have
+ "phones" which is another array of segments."""
+ self.segments = [Segment(s) for s in segments]
+ if self.segments:
+ self.type = self.segments[0].type
+ else:
+ self.type = None
+ self.sils = sils
+ self.orig = segments ## in case we want to have access to the original recognition structure
+
+ def __getitem__(self, item):
+ return self.segments[item]
+
+ def __repr__(self):
+ ns = len(self.segments)
+ res = "Segmentation with %d %s%s" % (ns, self.type, "" if ns==1 else "s")
+ for seg in self.segments:
+ res += "\n " + repr(seg)
+ return res
+
+ def __len__(self):
+ return len(self.segments)
+
+ def score(self, skip=None):
+ if not skip:
+ skip = self.sils
+ s = 0.0
+ for seg in self.segments:
+ if seg.label not in skip:
+ s += seg.score
+ return s
+
+ def llhs(self, skip=None):
+ if not skip:
+ skip = self.sils
+ return [seg.llh for seg in self.segments if hasattr(seg, "llh") and seg.label not in skip]
+
+ def llh(self, skip=None):
+ return sum(self.llhs(skip))
+
+ def minllh(self, skip=None):
+ llhs = self.llhs(skip)
+ if llhs:
+ return min(llhs)
+ else:
+ return None
+
+ def labels(self, skip=None):
+ if not skip:
+ skip = self.sils
+ return [seg.label for seg in self.segments if seg.label not in skip]
+
+ def sentence(self, skip=None):
+ return " ".join(self.labels(skip))
+
+ def export(self):
+ return [seg.export() for seg in self.segments]
\ No newline at end of file
diff --git a/novoapi/asr/spraaklab/__init__.py b/novoapi/asr/spraaklab/__init__.py
new file mode 100644
index 0000000..2c5f2fd
--- /dev/null
+++ b/novoapi/asr/spraaklab/__init__.py
@@ -0,0 +1,4 @@
+#!/usr/bin/env python
+
+#import schema
+from . import schema
\ No newline at end of file
diff --git a/novoapi/asr/spraaklab/schema.py b/novoapi/asr/spraaklab/schema.py
new file mode 100644
index 0000000..8efc49f
--- /dev/null
+++ b/novoapi/asr/spraaklab/schema.py
@@ -0,0 +1,273 @@
+#!/usr/bin/env python
+## (c) 2017 NovoLanguage, author: David A. van Leeuwen
+
+## The purpose of this to define the grammar structure in a json schema, so that it can be validated,
+## (de)serialized, and perhaps even automatically converted to a Python class structure.
+
+import json
+import jsonschema
+
+grammar_schema_v10 = {
+ "$schema": "http://json-schema.org/schema#",
+ "title": "NovoLanguage grammar",
+ "description": "A grammar specification for the NovoLanguage Automatic Speech Recognition",
+ "$ref": "#/definitions/group",
+ "definitions": {
+ "phones": {
+ "type": "array",
+ "items": {
+ "type": "string"
+ },
+ "minItems": 1
+ },
+ "pronunciation": {
+ "type": "object",
+ "properties": {
+ "phones": {
+ "$ref": "#/definitions/phones"
+ },
+ "syllables": {
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/syllable"
+ },
+ "minItems": 1
+ },
+ "id": {
+ "type": "integer",
+ "description": "ID to distinguish this pronunciation from other variants"
+ },
+ "meta": {
+ "type": "object"
+ }
+ },
+ "required": ["phones"]
+ },
+ "syllable": {
+ "type": "object",
+ "properties": {
+ "begin": {
+ "type": "integer",
+ "minimum": 0
+ },
+ "end": {
+ "type": "integer",
+ "minimum": 0
+ },
+ "stress": {
+ "type": "integer",
+ "minimum": 0
+ },
+ "tone": {
+ "type": "integer",
+ "minimum": 0
+ }
+ },
+ "required": ["begin", "end"]
+ },
+ "word": {
+ "type": "object",
+ "properties": {
+ "kind": {
+ "type": "string",
+ "enum": ["word"]
+ },
+ "label": {
+ "type": "string"
+ },
+ "pronunciation": {
+ "anyOf": [
+ {
+ "$ref": "#/definitions/pronunciation"
+ },
+ {
+ "type": "array",
+ "items": {
+ "anyOf": [
+ {
+ "$ref": "#/definitions/pronunciation"
+ },
+ {
+ "$ref": "#/definitions/phones"
+ }
+ ]
+ },
+ "minItems": 1
+ },
+ {
+ "$ref": "#/definitions/phones"
+ }
+
+ ]
+ },
+ "syllables": {
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/syllable"
+ }
+ },
+ "graphemes": {
+ "type": "array",
+ "items": {
+ "type": "string"
+ }
+ },
+ "id": {
+ "type": "integer",
+ "description": "ID to distinguish this word from other words (with possibly the same label)"
+ },
+ "meta": {
+ "type": "object"
+ }
+ },
+ "required": ["label"]
+ },
+ "element": {
+ "title": "element",
+ "oneOf": [
+ {
+ "$ref": "#/definitions/word"
+ },
+ {
+ "$ref": "#/definitions/group"
+ },
+ {
+ "type": ["string", "null"]
+ }
+ ]
+ },
+ "group": {
+ "title": "element group",
+ "type": "object",
+ "properties": {
+ "kind": {
+ "type": "string",
+ "enum": ["sequence", "alternatives", "order"]
+ },
+ "elements": {
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/element"
+ },
+ "minItems": 1,
+ },
+ "meta": {
+ "type": "object"
+ }
+ },
+ "required": ["kind", "elements"]
+ }
+ }
+}
+
+grammar_schema_v01 = {
+ "$schema": "http://json-schema.org/schema#",
+ "title": "NovoLanguage grammar v0.1",
+ "description": "A grammar specification for the NovoLanguage Automatic Speech Recognition",
+ "type": "object",
+ "properties": {
+ "type": {
+ "type": "string",
+ "enum": ["multiple_choice", "word_order"]
+ },
+ "parts": {
+ "type": "array",
+ "minItems": 1,
+ "maxItems": 5,
+ "items": {
+ "type": ["string", "array"],
+ "items": {
+ "type": ["string"]
+ }
+ }
+ }
+ }
+}
+
+grammar_rpc_schema = {
+ "$schema": "http://json-schema.org/schema#",
+ "title": "NovoLanguage RPC grammar",
+ "type": "object",
+ "properties": {
+ "type": {
+ "type": "string",
+ "enum": ["confusion_network"]
+ },
+ "version": {
+ "type": "string",
+ "default": "v0.1"
+ },
+ "data": {
+ "type": "object"
+ },
+ "return_dict": {
+ "type": "boolean"
+ },
+ "return_objects": {
+ "type": "array",
+ "items": {
+ "type": "string",
+ "enum": ["dict", "grammar"]
+ }
+ },
+ "phoneset": {
+ "type": "string",
+ "enum": ["cmu69", "novo70", "mdbg115"]
+ },
+ "parallel_silence": {
+ "type": "boolean"
+ }
+ },
+ "required": ["type", "data"]
+}
+
+def validate(object, schema=grammar_schema_v10):
+ #if isinstance(object, basestring):
+ if isinstance(object, str):
+ object = json.loads(object)
+ if not isinstance(object, dict):
+ raise TypeError("Expected dict or json string")
+ try:
+ jsonschema.validate(object, schema)
+ except jsonschema.ValidationError:
+ return False
+ except Exception:
+ raise
+ else:
+ return True
+
+def validate_rpc_grammar(message):
+ """validate an rpc grammar message"""
+ if not validate(message, grammar_rpc_schema):
+ raise ValueError("Not a valid RPC grammar")
+ version = message.get("version", "0.1")
+ data = message["data"]
+ if version == "0.1":
+ if not validate(data, grammar_schema_v01):
+ raise ValueError("Not a valid grammar v0.1")
+ elif version == "1.0":
+ if not validate(data, grammar_schema_v10):
+ raise ValueError("Not a valid grammar v1.0")
+ else:
+ raise ValueError("Unsupported schema version")
+
+
+## test
+def test(data=None):
+ if not data:
+ data = {"kind": "sequence", "elements": [
+ {"kind": "alternatives", "elements": ["a plain string", "an alternative string"]},
+ {"kind": "word", "label": "a word", "pronunciation": {"phones": ["ah", "w", "er", "d"]}},
+ {"kind": "order", "elements": [{"kind": "word", "label": "another word", "visible": False}, "last word"]}]}
+ try:
+ jsonschema.validate(data, schema)
+ except jsonschema.ValidationError as e:
+ #print data, "validated not OK", e.message
+ print("{0} validated not OK {1}".format(data, e.message))
+ else:
+ #print data, "validated OK"
+ print("{} validated OK".format(data))
+
+
+if __name__ == "__main__":
+ test()
diff --git a/novoapi/backend/__init__.py b/novoapi/backend/__init__.py
new file mode 100644
index 0000000..c52d472
--- /dev/null
+++ b/novoapi/backend/__init__.py
@@ -0,0 +1,4 @@
+#!/usr/bin/env python
+
+#import session
+from . import session
\ No newline at end of file
diff --git a/novoapi/backend/session.py b/novoapi/backend/session.py
new file mode 100644
index 0000000..b08a096
--- /dev/null
+++ b/novoapi/backend/session.py
@@ -0,0 +1,254 @@
+#!/usr/bin/env python
+# (c) 2015--2018 NovoLanguage, author: David A. van Leeuwen
+
+## Recognition interface for actual backend. Adapted from player.asr.debug.
+
+import json
+import sys
+import wave
+import requests
+import websocket
+import logging
+import collections
+
+import time
+
+from .. import asr
+
+logger = logging.getLogger(__name__)
+
+## turn off annoying warnings
+requests.packages.urllib3.disable_warnings()
+logging.getLogger("requests.packages.urllib3.connectionpool").setLevel(logging.WARN)
+
+buffer_size = 4096
+gm = "gm.novolanguage.com" ## dev
+protocol = "https"
+port = 443
+apiversion = 0
+
+sessions = collections.Counter()
+
+def segmentation(result):
+ """converts a raw backend recognition result to a segment of novo.asr.segments class Segmentation"""
+ for w in result:
+ w["score"] = w["confidence"]["prob"]
+ w["llh"] = w["confidence"]["llr"]
+ w["label"] = w["label"]["raw"]
+ w["begin"] /= 10
+ w["end"] /= 10
+ for p in w["phones"]:
+ p["score"] = p["confidence"]["prob"]
+ p["llh"] = p["confidence"]["llr"]
+ p["begin"] /= 10
+ p["end"] /= 10
+ return asr.segments.Segmentation(result)
+
+class rpcid:
+ id = 0
+ @staticmethod
+ def next():
+ rpcid.id += 1
+ return rpcid.id
+
+class Recognizer(object):
+ def __init__(self, lang="en", gm=gm, grammar_version="0.1", user=None, password=None, snodeid=None, keepopen=False):
+ self.lang = lang
+ self.keepopen = keepopen
+ self.api_url = "%s://%s:%d/v%d" % (protocol, gm, port, apiversion)
+ self.verify = False
+ self.headers = {"Content-Type": "application/json"}
+ self.login_user(user, password)
+ data = {"l2": lang, "local": False, "skipupload": True}
+ if snodeid:
+ data["snodeid"] = snodeid
+ self.conn = None
+ self.init_session(data)
+ self.grammar_version = grammar_version
+ self.last_message = None
+
+ def login_user(self, username, password):
+ # obtain authentication token of user
+ logger.info('obtain auth token at %s', self.api_url)
+ data = {
+ 'username': username,
+ 'password': password
+ }
+ try:
+ r = requests.post(self.api_url + '/publishers/1/login', headers=self.headers, data=json.dumps(data), verify=self.verify)
+ except Exception as e:
+ logger.error("Cannot post request to GM API for user login: %s", e.message)
+ sys.exit(-1)
+ assert r.ok, r.reason
+ result = r.json()
+ if "errors" in result["response"]:
+ logger.info("Error in logging in: %s", result["response"]["errors"])
+ sys.exit(-1)
+
+ user_auth_token = result['response']['user']['authentication_token']
+ logger.info("User auth token is: %s", user_auth_token)
+
+ # set auth token in header
+ self.headers['Authentication-Token'] = user_auth_token
+
+ def init_session(self, data, direct=False, use_ip=False):
+ logger.info('Request new session: %s', data)
+ r = requests.post(self.api_url + '/sessions', headers=self.headers, data=json.dumps(data), verify=self.verify)
+ if not r.ok:
+ logger.error("New session request failed: %s", r.text)
+ return
+
+ status_url = r.headers.get("location")
+ if status_url:
+ ## we got a redirect
+ status = {}
+ while True:
+ logger.debug("Checking %s", status_url)
+ s = requests.get(status_url, verify=self.verify)
+ if not s.ok:
+ logger.error('Checking Failed: %s', s.text)
+ return
+
+ status = s.json()
+ if status['status'] == 'PENDING':
+ logger.debug("Status: %s", status['status'])
+ time.sleep(1)
+ else:
+ break
+ session = status['result'][0] ## [1] is another status code...
+ if "error" in session:
+ logger.error("Error in getting a snode: %s", session["error"])
+ raise Exception
+ else:
+ session = r.json()
+
+ try:
+ logger.info("Session: %r", session)
+ if direct:
+ snode_ip = session["snode"]["ip"]
+ proxy_url = snode_ip
+ snode_port = session["port"]
+ ws_url = "%s://%s:%d/" % ("ws", snode_ip, snode_port)
+ else:
+ field = "ip" if use_ip else "hostname"
+ proxy_url = session['snode']['datacentre']['proxy'][field]
+ ws_url = 'wss://' + proxy_url + '/' + session['uuid']
+ logger.info("Connecting to websocket: %s", ws_url)
+ conn = websocket.create_connection(ws_url, sslopt={"check_hostname": self.verify})
+ logger.info("Connected.")
+ #except Exception, e:
+ except Exception as e:
+ logger.error("Unable to connect to websocket: %s", e.message)
+ raise e
+
+ self.session_id = session['id']
+ self.proxy_url = proxy_url
+ self.conn = conn
+ self.session = session
+ sessions[session["uuid"]] += 1
+
+ def setgrammar(self, grammar): ## backend grammar object: {"data": {...}, "type": "confusion_network"}
+ data = {"jsonrpc": "2.0",
+ 'type': 'jsonrpc',
+ 'method': 'set_grammar',
+ 'params': grammar,
+ "id": rpcid.next()}
+ asr.spraaklab.schema.validate_rpc_grammar(grammar)
+ self.conn.send(json.dumps(data))
+ result = json.loads(self.conn.recv())
+ if result.get("error"):
+ logger.error("Exercise validation error: %s", result)
+ return result
+
+ def set_alternatives_grammar(self, *args, **kwargs):
+ if not "version" in kwargs:
+ kwargs["version"] = self.grammar_version
+ return self.setgrammar(alternatives_grammar(*args, **kwargs))
+
+ def recognize_wav(self, wavf):
+ w = wave.open(wavf, 'r')
+ nchannels, sampwidth, framerate, nframes, comptype, compname = w.getparams()
+ if nchannels > 1:
+ logging.error("Please use .wav with only 1 channel, found %d channels in %s", nchannels, wavf)
+ return
+ if (sampwidth != 2):
+ logging.error("Please use .wav with 2-byte PCM data, found %d bytes in %s", sampwidth, wavf)
+ return
+ if (framerate != 16000.0):
+ logging.error("Please use .wav sampled at 16000 Hz, found %1.0f in %s", framerate, wavf)
+ return
+ if (comptype != 'NONE'):
+ logging.error("Please use .wav with uncompressed data, found %s in %s", compname, wavf)
+ return
+ buf = w.readframes(nframes)
+ w.close()
+ return self.recognize_data(buf)
+
+ def recognize_data(self, buf):
+ nbytes_sent = 0
+ start = time.time()
+ for j in range(0, len(buf), buffer_size):
+ audio_packet = str(buf[j:j + buffer_size])
+ nbytes_sent += len(audio_packet)
+ self.conn.send_binary(audio_packet)
+ self.conn.send(json.dumps({"jsonrpc": "2.0", "method": "get_result", "id": rpcid.next()}))
+ logger.info("Waiting for recognition result...")
+ self.last_message = self.conn.recv() ## keep result for the interested applications
+ message = json.loads(self.last_message)
+ dur = time.time() - start
+ logger.info("Recognition took %5.3f seconds", dur)
+ if "error" in message:
+ raise RuntimeError("Error from recognition backend: %r" % message.get("error"))
+ return segmentation(message["result"]["words"])
+
+ def recognize_url(self, url):
+ start = time.time()
+ data = json.dumps({"jsonrpc": "2.0", "method": "send_audio", "id": rpcid.next(), "params": {"type": "url", "data": url, "details": ["word", "utterance"]}})
+ self.conn.send(data)
+ logger.info("Waiting for recognition result...")
+ self.last_message = self.conn.recv() ## keep result for the interested applications
+ #print self.last_message
+ print(self.last_message)
+ message = json.loads(self.last_message)
+ dur = time.time() - start
+ logger.info("Recognition took %5.3f seconds", dur)
+ if "error" in message:
+ raise RuntimeError("Error from recognition backend: %r" % message.get("error"))
+ return segmentation(message["result"]["words"])
+
+ def __del__(self):
+ sessions[self.session["uuid"]] -= 1
+ if self.conn and sessions[self.session["uuid"]] <= 0:
+ self.conn.close()
+ url = self.api_url + '/sessions/%d' % self.session_id
+ if self.keepopen:
+ logger.info("Keeping session open...")
+ else:
+ logger.info("Closing session: %s", url)
+ r = requests.delete(url, headers=self.headers, verify=self.verify)
+ assert r.ok, r.reason
+
+def alternatives_grammar(parts, version="0.1", ret=None):
+ """Make a grammar of alternatives, as array(sequence)-of-array(alternatives)-of-strings"""
+ r = {"type": "confusion_network", "version": version}
+ if version=="0.1":
+ r["data"] = {"type": "multiple_choice", "parts": parts}
+ if isinstance(ret, list) and "dict" in ret:
+ r["return_dict"] = True
+ elif version=="1.0":
+ seqels = []
+ for part in parts:
+ altels = []
+ for alt in part:
+ words = alt.split(" ")
+ if len(words) > 1:
+ alt = {"kind": "sequence", "elements": words}
+ altels.append(alt)
+ seqels.append({"kind": "alternatives", "elements": altels})
+ r["data"] = {"kind": "sequence", "elements": seqels}
+ if isinstance(ret, list):
+ r["return_objects"] = ret
+ else:
+ raise ValueError("Unsupported version: %s" % version)
+ asr.spraaklab.schema.validate_rpc_grammar(r)
+ return r
diff --git a/novoapi/utils/json/__init__.py b/novoapi/utils/json/__init__.py
new file mode 100644
index 0000000..75d0b5f
--- /dev/null
+++ b/novoapi/utils/json/__init__.py
@@ -0,0 +1,25 @@
+#!/usr/bin/env python
+
+## from https://stackoverflow.com/questions/1447287/format-floats-with-standard-json-module
+class PrettyFloat(float):
+ def __repr__(self):
+ return '%.15g' % self
+
+def pretty_floats(obj):
+ if isinstance(obj, float):
+ return PrettyFloat(obj)
+ elif isinstance(obj, dict):
+ return dict((k, pretty_floats(v)) for k, v in obj.items())
+ elif isinstance(obj, (list, tuple)):
+ return map(pretty_floats, obj)
+ return obj
+
+def rounded_floats(obj, ndigits=15):
+ if isinstance(obj, float):
+ return PrettyFloat(round(obj, ndigits))
+ elif isinstance(obj, dict):
+ return dict((k, rounded_floats(v, ndigits)) for k, v in obj.items())
+ elif isinstance(obj, (list, tuple)):
+ return map(lambda o: rounded_floats(o, ndigits), obj)
+ return obj
+