###### Abstract  
Electro-laryngeal (EL) speech has poor intelligibility and naturalness, which hampers the popular use of the electro-larynx. Voice conversion (VC) can enhance EL speech. However, if the EL speech to be enhanced is with complicated tone variation rules in Mandarin, the enhancement will be less effective. This is because the source speech (Mandarin EL speech) and the target speech (normal speech) are not strictly parallel. We propose using cycle-consistent generative adversarial networks (CycleGAN, a parallel-free VC framework) to enhance continuous Mandarin EL speech, which can solve the above problem. In the proposed framework, the generator is designed based on the neural networks of a 2D-Conformer-1D-Transformer-2D-Conformer. Then, we used Mel-Spectrogram instead of traditional acoustic features (fundamental frequency, Mel-Cepstrum parameters and aperiodicity parameters). At last, we converted the enhanced Mel-Spectrogram into waveform signals using WaveNet. We undertook both subjective and objective tests to evaluate the proposed approach. Compared with traditional approaches to enhance continuous Mandarin EL speech with variable tone (the average tone accuracy being 71.59% and average word error rate being 10.85%), our framework increases the average tone accuracy by 12.12% and reduces the average errors of word perception by 9.15%. Compared with the approaches towards continuous Mandarin EL speech with fixed tone (the average tone accuracy being 29.89% and the average word error rate being 10.74%), our framework increases the average tone accuracy by 42.38% and reduces the average errors of word perception by 8.59%. Our proposed framework can effectively address the problem that the source and target speech are not strictly parallel. The intelligibility and naturalness of Mandarin EL speech have been further improved. M +
Footnote †: journal: _Applied Sciences_  
To improve the intelligibility and naturalness of EL speech, researchers have tried multiple approaches. During the early stage, researchers mainly tried to improve the electro-larynx, exploring an electro-larynx controlled by biophysical signals. For instance, researches tried to improve the flexibility of F0 variation through applying vocal air pressure signals [4], neck strap muscle electromyographically activity signals [5; 6], finger pressure signals [7] or finger sliding signals [8; 9]. Meanwhile, radiation noise is still an important factor that influences the intelligibility of EL speech. In this regard, researchers tried to reduce the radiation noise through various approaches including noise cancelling based on adaptive filter [10; 11; 12] and spectral subtraction [13; 14; 15]. The enhancement of Mandarin EL speech is different from the enhancement of normal speech with background noise [16; 17; 18], for that the Mandarin EL speech has the drawbacks of radiation noise and tone errors [1; 2; 3], which make it more difficult to deal with. Signal processing methods can effectively reduce the radiation noise of Mandarin EL speech [10; 11; 12; 13; 14; 15]. However, traditional approaches of improving the F0-controllable electro-larynx (this approach cannot reduce the radiation noise) or reducing radiation noise through signal processing (this approach cannot improve the flexibility of F0 variation) still have deficiencies in making EL speech more intelligible and natural. Recently, researchers applied frame-by-frame voice conversion (VC, parallel-dependent VC) to improve the intelligibility and naturalness of the EL speech [19; 20; 21; 22]. However, this parallel-dependent VC approach is still deficient in enhancing Mandarin EL speech. This deficiency is due to the complicated tone-variation rules of Mandarin EL speech and is more prominent when the Mandarin EL speech is pronounced using a finger-pressed electro-larynx at fixed tone [23].