Speech Recognition Using Tacotron

Motivation

Tacotron is an end-to-end speech generation model which was first introduced in Towards End-to-End Speech Synthesis. It takes as input text at the character level, and targets mel filterbanks and the linear spectrogram. Although it is a generation model, I felt like testing how well it can be applied to the speech recognition task.

Requirements

• NumPy >= 1.11.1
• TensorFlow == 1.1
• librosa

Model description

Tacotron—Speech Synthesis Model (From_ Figure 1 in Towards End-to-End Speech Synthesis)

Data

The World English Bible is a public domain update of the American Standard Version of 1901 into modern English. Its text and audio recordings are freely available here. Unfortunately, however, each of the audio files matches a chapter, not a verse, so is too long for many machine learning tasks. I had someone slice them by verse manually. You can download the audio data and its text from my dropbox.

File description

• hyperparams.py includes all hyper parameters.
• prepro.py creates training and evaluation data to data/ folder.
• data_load.py loads data and put them in queues so multiple mini-bach data are generated in parallel.
• utils.py has some operational functions.
• modules.py contains building blocks for encoding and decoding networks.
• networks.py defines encoding and decoding networks.
• train.py executes training.
• eval.py executes evaluation.

Training

• STEP 1. Adjust hyper parameters in hyperparams.py if necessary.
• STEP 2. Download and extract the audio data and its text.
• STEP 3. Run train.py. Or you can download my pretrained file

Evaluation

• Run eval.py to get speech recognition results for the test set.

Results

The training curve looks like

Sample results are

Expected: the third poured out his bowl into the rivers and springs of water and they became blood
Got : the first will lie down to the rivers and springs of waters and it became blood

Expected: i heard the altar saying yes lord god the almighty true and righteous are your judgments
Got : i heard the altar saying yes were like your own like you tree in righteousness for your judgments

Expected: the fourth poured out his bowl on the sun and it was given to him to scorch men with fire
Got : the foolish very armed were on the sun and was given to him to spoke to him with fire

Expected: he gathered them together into the place which is called in hebrew megiddo
Got : he gathered them together into the place which is called and he weep and at every

Expected: every island fled away and the mountains were not found
Got : hadad and kedemoth aroen and another and spread out them

Expected: here is the mind that has wisdom the seven heads are seven mountains on which the woman sits
Got : he is the mighty have wisdom the seven heads of seven rountains are with the wind sixter

Expected: these have one mind and they give their power and authority to the beast
Got : these are those who are mine and they give holl of a fool in the deeps

Expected: the woman whom you saw is the great city which reigns over the kings of the earth
Got : the woman whom he saw it his degrection which ran and to advening to be ear

Expected: for her sins have reached to the sky and god has remembered her iniquities
Got : for he sends a least in the sky and god has remembered her iniquities

Expected: the merchants of the earth weep and mourn over her for no one buys their merchandise any more
Got : the mittites of the earth weeps in your own are before from knowing babylon busine backsliding all t

Expected: and cried out as they looked at the smoke of her burning saying 'what is like the great city'
Got : and cried all the wicked beside of a good one and saying when is like the great sight

Expected: in her was found the blood of prophets and of saints and of all who have been slain on the earth
Got : and her with stones a dwellified confidence and all who have been slain on the earth

Expected: a second said hallelujah her smoke goes up forever and ever
Got : as set him said how many men utter for smoke go down for every male it

Expected: he is clothed in a garment sprinkled with blood his name is called the word of god
Got : he is close in a garment speaking in the blood his name is called 'the word of god'

Expected: the armies which are in heaven followed him on white horses clothed in white pure fine linen
Got : the army which are in heaven falls on the mighty one horses clothes driven on the affliction

Expected: he has on his garment and on his thigh a name written king of kings and lord of lords
Got : he has understandings on his folly among widow the king of kings and yahweh of armies

Expected: i saw an angel coming down out of heaven having the key of the abyss and a great chain in his hand
Got : i saw an even become young lion having you trust of the ages and a great chamber is hand

Expected: and after the thousand years satan will be released from his prison
Got : and after the palace and mizpah and eleven eleenth were the twentieth

Expected: death and hades were thrown into the lake of fire this is the second death the lake of fire
Got : let them hate with one and to wait for fire this is the second death and lead a time

Expected: if anyone was not found written in the book of life he was cast into the lake of fire
Got : the ten man will not think within your demon as with a blood he will cast him to ram for fire

Expected: he who overcomes i will give him these things i will be his god and he will be my son
Got : he who recompenses i will give him be stings i will be his god and he will be my son

Expected: its wall is one hundred fortyfour cubits by the measure of a man that is of an angel
Got : is through all his womb home before you for accusation that we may know him by these are in egypt

Expected: the construction of its wall was jasper the city was pure gold like pure glass
Got : if he struck him of his wallor is not speaking with torment hold on her grass

Expected: i saw no temple in it for the lord god the almighty and the lamb are its temple
Got : i saw in a tenth wind for we will dry up you among the linen ox skillful

Expected: its gates will in no way be shut by day for there will be no night there
Got : his greech wind more redeems shameful the redeemer man don't know

Expected: and they shall bring the glory and the honor of the nations into it so that they may enter
Got : and they shall bring the glory in the high mountains and the egyptian into the midst of the needy

Expected: they will see his face and his name will be on their foreheads
Got : they will see his face and his name on their follows

Expected: behold i come quickly blessed is he who keeps the words of the prophecy of this book
Got : behold i happened with me when i could see me to still it is a prophet his bueld

Expected: he said to me don't seal up the words of the prophecy of this book for the time is at hand
Got : he said to him why sil with the words of the prophets it is book for the times and her

Expected: behold i come quickly my reward is with me to repay to each man according to his work
Got : behold i come perfect i yahweh is with me to repent to be shamed according to his work

Expected: i am the alpha and the omega the first and the last the beginning and the end
Got : i have you hope from you and you and the first from aloes of the dew and the enemy

Expected: he who testifies these things says yes i come quickly amen yes come lord jesus
Got : he who testifies these things says yes i come proclaim i man listen will jesus

Related projects

• A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model
• Speech-to-Text-WaveNet : End-to-end sentence level English speech recognition based on DeepMind's WaveNet and tensorflow