/external/webrtc/webrtc/common_audio/vad/ |
D | vad_core_unittest.cc | 59 int16_t speech[kMaxFrameLength]; in TEST_F() local 66 memset(speech, 0, sizeof(speech)); in TEST_F() 70 EXPECT_EQ(0, WebRtcVad_CalcVad8khz(self, speech, kFrameLengths[j])); in TEST_F() 73 EXPECT_EQ(0, WebRtcVad_CalcVad16khz(self, speech, kFrameLengths[j])); in TEST_F() 76 EXPECT_EQ(0, WebRtcVad_CalcVad32khz(self, speech, kFrameLengths[j])); in TEST_F() 79 EXPECT_EQ(0, WebRtcVad_CalcVad48khz(self, speech, kFrameLengths[j])); in TEST_F() 86 speech[i] = static_cast<int16_t>(i * i); in TEST_F() 90 EXPECT_EQ(1, WebRtcVad_CalcVad8khz(self, speech, kFrameLengths[j])); in TEST_F() 93 EXPECT_EQ(1, WebRtcVad_CalcVad16khz(self, speech, kFrameLengths[j])); in TEST_F() 96 EXPECT_EQ(1, WebRtcVad_CalcVad32khz(self, speech, kFrameLengths[j])); in TEST_F() [all …]
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D | vad_filterbank_unittest.cc | 40 int16_t speech[kMaxFrameLength]; in TEST_F() local 42 speech[i] = static_cast<int16_t>(i * i); in TEST_F() 50 WebRtcVad_CalculateFeatures(self, speech, kFrameLengths[j], in TEST_F() 62 memset(speech, 0, sizeof(speech)); in TEST_F() 66 EXPECT_EQ(0, WebRtcVad_CalculateFeatures(self, speech, kFrameLengths[j], in TEST_F() 77 speech[i] = 1; in TEST_F() 82 EXPECT_EQ(0, WebRtcVad_CalculateFeatures(self, speech, kFrameLengths[j], in TEST_F()
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D | vad_unittest.cc | 67 int16_t speech[kMaxFrameLength]; in TEST_F() local 69 speech[i] = static_cast<int16_t>(i * i); in TEST_F() 76 WebRtcVad_Process(nullptr, kRates[0], speech, kFrameLengths[0])); in TEST_F() 82 EXPECT_EQ(-1, WebRtcVad_Process(handle, kRates[0], speech, kFrameLengths[0])); in TEST_F() 102 EXPECT_EQ(-1, WebRtcVad_Process(handle, 9999, speech, kFrameLengths[0])); in TEST_F() 114 speech, in TEST_F() 119 speech, in TEST_F()
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/external/tensorflow/tensorflow/lite/models/testdata/g3doc/ |
D | README.md | 3 Sample test data has been provided for speech related models in Tensorflow Lite 4 to help users working with speech models to verify and test their models. 42 For the hotword, speaker-id and automatic speech recognition sample models, the 43 architecture assumes that the models receive their input from a speech 44 pre-processing module. The speech pre-processing module receives the audio 48 applied to the power spectra). The text-to-speech model assumes that the inputs 63 The speech hotword model block diagram is shown in Figure below. It has an input 72 verification. It runs after the hotword triggers. The speech speaker-id model 79 ### Text-to-speech (TTS) Model 81 The text-to-speech model is the neural network model used to generate speech [all …]
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/external/webrtc/webrtc/modules/audio_coding/codecs/pcm16b/ |
D | pcm16b.c | 15 size_t WebRtcPcm16b_Encode(const int16_t* speech, in WebRtcPcm16b_Encode() argument 20 uint16_t s = speech[i]; in WebRtcPcm16b_Encode() 29 int16_t* speech) { in WebRtcPcm16b_Decode() argument 32 speech[i] = encoded[2 * i] << 8 | encoded[2 * i + 1]; in WebRtcPcm16b_Decode()
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D | pcm16b.h | 41 size_t WebRtcPcm16b_Encode(const int16_t* speech, 62 int16_t* speech);
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/external/sl4a/Common/src/com/googlecode/android_scripting/facade/ |
D | SpeechRecognitionFacade.java | 20 import android.speech.RecognizerIntent; 52 new Intent(android.speech.RecognizerIntent.ACTION_RECOGNIZE_SPEECH); in recognizeSpeech() 68 if (data.hasExtra(android.speech.RecognizerIntent.EXTRA_RESULTS)) { in recognizeSpeech() 72 data.getStringArrayListExtra(android.speech.RecognizerIntent.EXTRA_RESULTS); in recognizeSpeech()
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D | TextToSpeechFacade.java | 20 import android.speech.tts.TextToSpeech; 21 import android.speech.tts.TextToSpeech.OnInitListener;
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/external/sonic/doc/ |
D | index.md | 21 Sonic is free software for speeding up or slowing down speech. While similar to 34 to improve their productivity with free software speech engines, like espeak. 48 In short, Sonic is better for speech, while WSOLA is better for music. 52 for speech (contrary to the inventor's estimate of WSOLA). Listen to [this 55 introduces unacceptable levels of distortion, making speech impossible to 58 However, there are decent free software algorithms for speeding up speech. They 59 are all in the TD-PSOLA family. For speech rates below 2X, sonic uses PICOLA, 131 double speed of speech. A pitch of 0.95 means to lower the pitch by about 5%, 134 speech is played. A 2.0 value will make you sound like a chipmunk talking very 153 You read the sped up speech samples from sonic like this:
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/external/autotest/client/site_tests/desktopui_SpeechSynthesisSemiAuto/ |
D | desktopui_SpeechSynthesisSemiAuto.py | 20 speech = dbus.Interface(proxy, "org.chromium.SpeechSynthesizerInterface") 21 res = speech.Speak("Welcome to Chromium O S")
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/external/robolectric-shadows/shadows/framework/src/main/java/org/robolectric/shadows/ |
D | ShadowTextToSpeech.java | 10 import android.speech.tts.TextToSpeech; 11 import android.speech.tts.TextToSpeech.Engine; 12 import android.speech.tts.UtteranceProgressListener;
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/external/sonic/debian/ |
D | control | 14 Description: Simple utility to speed up or slow down speech 24 Description: Simple library to speed up or slow down speech 27 down speech. It has only basic dependencies, and is meant to
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/external/sonic/ |
D | README | 1 Sonic is a simple algorithm for speeding up or slowing down speech. However, 3 speech rate. The Sonic library is a very simple ANSI C library that is designed 7 to improve their productivity with open source speech engines, like espeak.
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/external/webrtc/resources/audio_coding/ |
D | READ.ME | 3 testfile32kHz.pcm - mono speech file samples at 32 kHz 4 teststereo32kHz.pcm - stereo speech file samples at 32 kHz
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/external/robolectric-shadows/robolectric/src/test/java/org/robolectric/shadows/ |
D | ShadowTextToSpeechTest.java | 11 import android.speech.tts.TextToSpeech; 12 import android.speech.tts.TextToSpeech.Engine; 13 import android.speech.tts.UtteranceProgressListener;
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/external/webrtc/webrtc/modules/audio_coding/codecs/cng/ |
D | audio_encoder_cng_unittest.cc | 273 EXPECT_FALSE(encoded_info_.speech); in TEST_F() 294 EXPECT_TRUE(encoded_info_.speech); in TEST_F() 299 EXPECT_TRUE(encoded_info_.speech); in TEST_F() 304 EXPECT_TRUE(encoded_info_.speech); in TEST_F() 308 EXPECT_FALSE(encoded_info_.speech); in TEST_F()
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D | webrtc_cng.h | 106 int WebRtcCng_Encode(CNG_enc_inst* cng_inst, int16_t* speech,
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_Mfcc.pbtxt | 42 summary: "Transforms a spectrogram into a form that\'s useful for speech recognition." 48 history in the speech recognition world, and https://en.wikipedia.org/wiki/Mel-frequency_cepstrum
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/external/webrtc/webrtc/modules/audio_coding/codecs/red/ |
D | audio_encoder_copy_red.cc | 81 RTC_DCHECK_EQ(info.speech, info.redundant[0].speech); in EncodeInternal()
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/external/libgsm/ |
D | README | 2 GSM 06.10 13 kbit/s RPE/LTP speech compression available 11 European GSM 06.10 provisional standard for full-rate speech
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D | METADATA | 2 description: "Lossy speech compression."
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/external/sonic/samples/ |
D | README | 1 These wav files show how Sonic performs at increasing speech rates. All sound 20 Sonic also performs well at increasing the speed of synthesized speech.
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/external/tensorflow/tensorflow/examples/speech_commands/ |
D | README.md | 3 This is a basic speech recognition example. For more information, see the
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/external/speex/ |
D | speexdsp.pc.in | 9 Description: Speexdsp is a speech processing library that goes along with the Speex codec
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/external/webrtc/webrtc/modules/audio_coding/codecs/ |
D | audio_encoder.h | 31 bool speech = true; member
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