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MultiNet Introduction
MultiNet is a lightweight model specially designed based on CRNN and CTC for the implementation of multi-command recognization. Now, up to 200 speech commands, including customized commands, are supported.
Overview
MultiNet uses the MFCC features of an audio clip as input, and the phonemes (Chinese or English) as output. By comparing the output phonemes, the relevant Chinese or English command is identified.
The following table shows the model support of Espressif SoCs:
Commands Recognition Process
- Add customized commands to the speech command queue.
- Prepare an audio clip of 30 ms (16 KHz, 16 bit, mono).
- Input this audio to the MFCC model and get its MFCC features.
- Input the obtained MFCC features to MultiNet and get the output phoneme.
- Input the obtained phoneme to the Language model and get the output.
- Compare the output against the existing speech commands one by one, and output the Command ID of the matching command (if any).
Please see the flow diagram below:
User Guide
Basic Configuration
Define the following two variables before using the command recognition model:
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Model version
The model version has been configured inmenuconfigto facilitate your development. Please configure inmenuconfigand add the following line in your code:static const esp_mn_iface_t *multinet = &MULTINET_MODEL; -
Model parameter
The language supported and the effectiveness of the model is determined by model parameters. Now only commands in Chinese are supported. Please configure theMULTINET_COEFFoption inmenuconfigand add the following line in your code to generate the model handle. The 6000 is the audio length for speech recognition, in ms, the range of sample_length is 0~6000.model_iface_data_t *model_data = multinet->create(&MULTINET_COEFF, 6000);
Modify Speech Commands
For Chinese MultiNet, we use Pinyin without tone as units. For English MultiNet, we use international phonetic alphabet as unit. multinet_g2p.py is used to convert English phrase into phonemes which can be recognized by multinet. Now, the MultiNet support two methods to modify speech commands.
1.menuconfig (before compilation)
Users can define their own speech commands by idf.py menuconfig -> ESP Speech Recognition -> add speech commands
2.reset API (on the fly)
Users also can modify speech commands in the code.
// Chinese
char err_id[200];
char *ch_commands_str = "da kai dian deng,kai dian deng;guan bi dian deng,guan dian deng;guan deng;";
multinet->reset(model_data, ch_commands_str, err_id);
// English
char *en_commands_en = "TfL Mm c qbK;Sgl c Sel;TkN nN jc LiT;TkN eF jc LiT";
multinet->reset(model_data, en_commands_en, err_id);
Note:
- One speech commands ID can correspond to multiple speech command phrases;
- Up to 200 speech commands ID or speech command phrases, including customized commands, are supported;
- Different Command IDs need to be separated by ';'. The corresponding multiple phrases for one Command ID need to be separated by ','.
err_idreturn the spelling that does not meet the requirements.
API Reference
Header
- esp_mn_iface.h
- esp_mn_models.h
Function
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typedef model_iface_data_t* (*esp_mn_iface_op_create_t)(const model_coeff_getter_t *coeff, int sample_length);Definition
Easy function type to initialize a model instance with a coefficient.
Parameter
- coeff: The coefficient for speech commands recognition.
- sample_length: Audio length for speech recognition, in ms. The range of sample_length is 0~6000.
Return
Handle to the model data.
-
typedef int (*esp_mn_iface_op_get_samp_chunksize_t)(model_iface_data_t *model);Definition
Callback function type to fetch the amount of samples that need to be passed to the detection function. Every speech recognition model processes a certain number of samples at the same time. This function can be used to query the amount. Note that the returned amount is in 16-bit samples, not in bytes.
Parameter
model: The model object to query.
Return
The amount of samples to feed the detection function.
-
typedef int (*esp_mn_iface_op_get_samp_chunknum_t)(model_iface_data_t *model);Definition
Callback function type to fetch the number of frames recognized by the speech command.
Parameter
model: The model object to query.
Return
The number of the frames recognized by the speech command.
-
typedef int (*esp_mn_iface_op_get_samp_rate_t)(model_iface_data_t *model);Definition
Get the sample rate of the samples to feed to the detection function.
Parameter
model: The model object to query.
Return
The sample rate, in Hz.
-
typedef float* (*esp_mn_iface_op_detect_t)(model_iface_data_t *model, int16_t *samples);Definition
Easy function type to initialize a model instance with a coefficient.
Parameter
coeff: The coefficient for speech commands recognition.
Return
- The command id, if a matching command is found.
- -1, if no matching command is found.
-
typedef void (*esp_mn_iface_op_reset_t)(model_iface_data_t *model, char *command_str, char *err_phrase_id);Definition
Reset the speech commands.
Parameters
model: Model object to destroy. command_str: The speech commands string. ';' is used to separate commands for different command ID. ',' is used to separate different phrases for same command ID. err_phrase_id: Return incorrent spelling
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typedef void (*esp_mn_iface_op_destroy_t)(model_iface_data_t *model);Definition
Destroy a voiceprint recognition model.
Parameters
model: Model object to destroy.



