diff --git a/src/losses/ctc.jl b/src/losses/ctc.jl
index 230d04add3..ff1183e99f 100644
--- a/src/losses/ctc.jl
+++ b/src/losses/ctc.jl
@@ -46,19 +46,19 @@ function ctc_alpha(ŷ::AbstractArray, y)
   α[1,1] = ŷ[blank, 1]
   α[2,1] = ŷ[z′[2], 1]
   for t=2:T
-	bound = max(1, U′ - 2(T - t) - 1)
+    bound = max(1, U′ - 2(T - t) - 1)
     for u=bound:U′
-	  if u == 1
-		α[u,t] = α[u, t-1]
-	  else
-		α[u,t] = logaddexp(α[u, t-1], α[u-1, t-1])
-		
-		# array bounds check and f(u) function from Eq. 7.9
-		if u > 2 && !(z′[u] == blank || z′[u-2] == z′[u])
-		  α[u,t] = logaddexp(α[u,t], α[u-2,t-1])
-		end
-	  end
-	  α[u,t] += ŷ[z′[u], t]
+      if u == 1
+        α[u,t] = α[u, t-1]
+      else
+      α[u,t] = logaddexp(α[u, t-1], α[u-1, t-1])
+      
+      # array bounds check and f(u) function from Eq. 7.9
+      if u > 2 && !(z′[u] == blank || z′[u-2] == z′[u])
+        α[u,t] = logaddexp(α[u,t], α[u-2,t-1])
+      end
+    end
+    α[u,t] += ŷ[z′[u], t]
     end
   end
   return (loss=-1 * logaddexp(α[end,T], α[end-1, T]), alpha=α, zprime=z′, logsoftyhat=ŷ)
@@ -80,18 +80,18 @@ function ∇ctc_loss(ŷ::AbstractArray, y, out)
   
   # start at T-1 so that β(T, u) = log(0) for all u < U′ - 1
   for t=(T-1):-1:1
-	bound = min(U′, 2t)
+    bound = min(U′, 2t)
     for u=bound:-1:1
-	  if u == U′
-		β[u,t] = ŷ[z′[u], t+1] + β[u, t+1]
-	  else
-		β[u,t] = logaddexp(ŷ[z′[u], t+1] + β[u, t+1], ŷ[z′[u+1], t+1] + β[u+1,t+1])
+      if u == U′
+        β[u,t] = ŷ[z′[u], t+1] + β[u, t+1]
+      else
+        β[u,t] = logaddexp(ŷ[z′[u], t+1] + β[u, t+1], ŷ[z′[u+1], t+1] + β[u+1,t+1])
 
-		# array bounds check and g(u) function from Eq. 7.16
-		if u+2 <= U′ && z′[u] != blank && z′[u] != z′[u+2]
-		  β[u,t] = logaddexp(β[u,t], ŷ[z′[u+2], t+1] + β[u+2, t+1])
-	    end
-	  end
+        # array bounds check and g(u) function from Eq. 7.16
+        if u+2 <= U′ && z′[u] != blank && z′[u] != z′[u+2]
+          β[u,t] = logaddexp(β[u,t], ŷ[z′[u+2], t+1] + β[u+2, t+1])
+        end
+      end
     end
   end
 
@@ -132,7 +132,7 @@ for mathematical details.
 ctc_loss(ŷ::AbstractArray, y) = ctc_alpha(ŷ, y).loss
 
 @adjoint function ctc_loss(ŷ, y)
-	out = ctc_alpha(ŷ, y)
-	ctc_loss_pullback(Δ) = (Δ .* ∇ctc_loss(ŷ, y, out), nothing)
-	return out.loss, ctc_loss_pullback
+  out = ctc_alpha(ŷ, y)
+  ctc_loss_pullback(Δ) = (Δ .* ∇ctc_loss(ŷ, y, out), nothing)
+  return out.loss, ctc_loss_pullback
 end