Hi,

I’m using latest master branches of MozillaTTS and related WaveRNN branch (https://github.com/erogol/WaveRNN)

I have trained a test model for WaveRNN vocoder and trying to use newly trained model in MozillaTTS for Tacotron1. My WaveRNN configuration is like this:

"{

“model_name”: “wavernn_4241_finetune_gaussian”,

“model_description”: “Gaussian model as in Clarinet”,

```
"audio":{
"audio_processor": "audio", // to use dictate different audio processors, if available.
// Audio processing parameters
"num_mels": 80, // size of the mel spec frame.
"num_freq": 1025, // number of stft frequency levels. Size of the linear spectogram frame.
"sample_rate": 16000, // wav sample-rate. If different than the original data, it is resampled.
"frame_length_ms": 50, // stft window length in ms.
"frame_shift_ms": 12.5, // stft window hop-lengh in ms.
"preemphasis": 0.98, // pre-emphasis to reduce spec noise and make it more structured. If 0.0, no -pre-emphasis.
"min_level_db": -100, // normalization range
"ref_level_db": 20, // reference level db, theoretically 20db is the sound of air.
"power": 1.5, // value to sharpen wav signals after GL algorithm.
"griffin_lim_iters": 60,// #griffin-lim iterations. 30-60 is a good range. Larger the value, slower the generation.
// Normalization parameters
"signal_norm": true, // normalize the spec values in range [0, 1]
"symmetric_norm": false, // move normalization to range [-1, 1]
"max_norm": 1, // scale normalization to range [-max_norm, max_norm] or [0, max_norm]
"clip_norm": true, // clip normalized values into the range.
"mel_fmin": 0.0, // minimum freq level for mel-spec. ~50 for male and ~95 for female voices. Tune for dataset!!
"mel_fmax": 8000.0, // maximum freq level for mel-spec. Tune for dataset!!
"do_trim_silence": false // KEEP ALWAYS FALSE
},
"distributed":{
"backend": "nccl",
"url": "tcp:\/\/localhost:54321"
},
"epochs": 10000,
"grad_clip": 1000,
"lr": 0.0001,
"warmup_steps": 100,
"batch_size": 32,
"checkpoint_step": 1000,
"print_step": 10,
"num_workers": 8,
"mel_len": 8,
"pad": 2,
"mulaw": true,
"use_aux_net": false,
"use_upsample_net": false,
"upsample_factors": [5, 5, 11],
"mode": "mold", // model with gaussian (gaus), misture of logistic dist (mold). or raw bit output (# bits)."
```

When I try to use this wavernn model together with tacotron1 model, as soon as I try a test synthesis over server, I got the following error:

“RuntimeError: size mismatch, m1: [1 x 1026], m2: [81 x 512] at /opt/conda/conda-bld/pytorch_1573049310284/work/aten/src/THC/generic/THCTensorMathBlas.cu:290”

The error stems from the following line in WaveRNN/models/wavernn.py line 246:

“x = self.I(x)”

Here, the size of “x” is [1 x 1026] while the size of “I” is [81 x 512]

the size of “I” is initialized in line:

“self.I = nn.Linear(feat_dims + 1, rnn_dims)”

and the size is naturally [81 x 512]

I wonder if the latest master branch of mozillaTTS is compatible with WaveRNN or if there is any other error I make.

Thanks in advance.