Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems

Neural models have become ubiquitous in automatic speech recognition systems. While neural networks are typically used as acoustic models in more complex systems, recent studies have explored end-to-end speech recognition systems based on neural networks, which can be trained to directly predict text from input acoustic features. Although such systems are conceptually elegant and simpler than traditional systems, it is less obvious how to interpret the trained models. In this work, we analyze the speech representations learned by a deep end-to-end model that is based on convolutional and recurrent layers, and trained with a connectionist temporal classification (CTC) loss. We use a pre-trained model to generate frame-level features which are given to a classifier that is trained on frame classification into phones. We evaluate representations from different layers of the deep model and compare their quality for predicting phone labels. Our experiments shed light on important aspects of the end-to-end model such as layer depth, model complexity, and other design choices.Comment: NIPS 201

Chitosan-Graft-Polyethylenimine/DNA Nanoparticles as Novel Non-Viral Gene Delivery Vectors Targeting Osteoarthritis

<div><p>The development of safe and efficient gene carriers is the key to the clinical success of gene therapy. The present study was designed to develop and evaluate the chitosan-graft-polyethylenimine (CP)/DNA nanoparticles as novel non-viral gene vectors for gene therapy of osteoarthritis. The CP/DNA nanoparticles were produced through a complex coacervation of the cationic polymers with pEGFP after grafting chitosan (CS) with a low molecular weight (Mw) PEI (Mw = 1.8 kDa). Particle size and zeta potential were related to the weight ratio of CP:DNA, where decreases in nanoparticle size and increases in surface charge were observed as CP content increased. The buffering capacity of CP was significantly greater than that of CS. The transfection efficiency of CP/DNA nanoparticles was similar with that of the Lipofectamine™ 2000, and significantly higher than that of CS/DNA and PEI (25 kDa)/DNA nanoparticles. The transfection efficiency of the CP/DNA nanoparticles was dependent on the weight ratio of CP:DNA (w/w). The average cell viability after the treatment with CP/DNA nanoparticles was over 90% in both chondrocytes and synoviocytes, which was much higher than that of PEI (25 kDa)/DNA nanoparticles. The CP copolymers efficiently carried the pDNA inside chondrocytes and synoviocytes, and the pDNA was detected entering into nucleus. These results suggest that CP/DNA nanoparticles with improved transfection efficiency and low cytotoxicity might be a safe and efficient non-viral vector for gene delivery to both chondrocytes and synoviocytes.</p></div

Intracellular distribution of Cy3-labeled pDNA/CP complexes was observed with a confocal fluorescence microscope in chondrocytes (a) and synoviocytes (b).

<p>(Panel 1) 0.5 h post-incubation; (Panel 2) 1 h post-incubation; (Panel 3) 2 h post-incubation; and (Panel 4) 4 h post-incubation. Row A shows the Cy3-labeled pDNA (red); row B shows the lysosomal (green); row C shows the nucleus (blue); and row D shows the overlap of A, B, and C rows content.</p

Representative ¹H NMR spectra of chitosan (CS) and CS-<i>g</i>-PEI (CP) in a mixture solution (D₂O/CD₃COOD (V_D2O: V_CD3COOD = 1∶1) at 40°C.

<p>Representative ¹H NMR spectra of chitosan (CS) and CS-<i>g</i>-PEI (CP) in a mixture solution (D₂O/CD₃COOD (V_D2O: V_CD3COOD = 1∶1) at 40°C.</p

Characteristic of prepared CS-g-PEI (CP).

<p>^a calculated from GPC.</p><p>^b calculated from ¹H NMR.</p

Gel retarding analysis of CP/DNA nanoparticles.

<p>Lane 1: DNA marker. Lane 2: naked DNA control. Lane 3–8: CP/DNA nanoparticles prepared at CP:DNA weight ratios of 1∶2, 1∶1, 2∶1, 3∶1, 4∶1, and 5∶1 (a); electrophoresis photo of CP/DNA nanoparticles prepared with CP:DNA weight ratio = 3 at different pH levels (b); electrophoresis of CS/DNA nanoparticles prepared with the CS:DNA weight ratio = 3 at different pH levels (c).</p

Cell viabilities of CP/DNA nanoparticles, CS/DNA nanoparticles, PEI/DNA nanoparticles, and Lipofectamine™ 2000 in primary chondrocytes (a) and synoviocytes (b).

<p>*<i>P</i><0.01 compared to PEI/DNA nanoparticles; **<i>P</i><0.01 compared to Lipofectamine™ 2000.</p

GPC Curves of chitosan (CS) and CS-g-PEI (CP).

<p>GPC Curves of chitosan (CS) and CS-g-PEI (CP).</p

<i>In vitro</i> transfection efficiency of CP/DNA nanoparticles.

<p>(a) <i>In vitro</i> transfection efficiency of CP/DNA nanoparticles in both chondrocytes and synoviocytes compared to that of naked pDNA, CS/DNA nanoparticles, PEI (25 kDa)/DNA nanoparticles, and Lipofectamine™ 2000 (n = 3; 48 h post-transfection; error bars represent standard deviation). *<i>P</i><0.01 when CP/DNA nanoparticles compared to CS/DNA nanoparticles transfected towards chondrocytes (n = 3); **<i>P</i><0.01 when CP/DNA nanoparticles compared to PEI (25 kDa)/DNA nanoparticles transfected towards synoviocytes (n = 3); # or ## <i>P</i>>0.05 when CP/DNA nanoparticles compared to Lipofectamine™ 2000 transfected towards chondrocytes or synoviocytes (n = 3). (b) Percentage of chondrocytes or synoviocytes transfected <i>in vitro</i> using CP/DNA nanoparticles as measured by flow cytometry 48 h post-transfection. The influence of CP:DNA weight ratios on the transfection efficiency was assessed 48 h post-transfection (n = 3; error bars represent standard deviation).</p

Physiochemical property of CP and CP/DNA nanoparticles.

<p>(a) SEM images of CP/DNA nanoparticles at CP:DNA weight ratio = 3; (b) the effect of CP:DNA weight ratios on the particle size and the zeta potential of resulting nanoparticles (n = 3; error bars represent standard deviation); (c) size distribution of CP/DNA complexes prepared at the CP:DNA weight ratio = 3 measured by Mastersizer 2000 laser diffractometer; (d) buffering capacities of PEI (25 kDa), CS, and CP copolymers.</p